Create a guide to setup access via SageMaker

Is your feature request related to a problem? Please describe.
I'd like to connect to a Neptune cluster. The easiest thing for me would be to launch a SageMaker notebook in that VPC and work on it. However, it seems like installing the extensions is not as straight-forward as a pip install.
Describe the solution you'd like
A guide on how to install all the required dependencies, via a lifecycle configuration if possible.

Thanks for submitting this ticket! This should just be a documentation change. Indeed, pip install is not sufficient since you also need to enable some things on the jupyter side, and we upload pip as a wheel which won't do those steps.
The recommended approach for Sagemaker would be to use our script found in s3:
s3://aws-neptune-notebook/graph_notebook.tar.gz
Here is a sample lifecycle configuration which makes use of it:
#!/bin/bash

sudo -u ec2-user -i <<'EOF'

echo "export GRAPH_NOTEBOOK_AUTH_MODE=DEFAULT" >> ~/.bashrc  # set to IAM instead of DEFAULT if cluster is IAM enabled
echo "export GRAPH_NOTEBOOK_HOST=CHANGE-ME" >> ~/.bashrc
echo "export GRAPH_NOTEBOOK_PORT=8182" >> ~/.bashrc
echo "export NEPTUNE_LOAD_FROM_S3_ROLE_ARN=" >> ~/.bashrc
echo "export AWS_REGION=us-west-2" >> ~/.bashrc

aws s3 cp s3://aws-neptune-notebook/graph_notebook.tar.gz /tmp/graph_notebook.tar.gz
rm -rf /tmp/graph_notebook
tar -zxvf /tmp/graph_notebook.tar.gz -C /tmp
/tmp/graph_notebook/install.sh

EOF

Updated docs to share sample lifecycle configuration file for use with SageMaker: https://github.com/aws/graph-notebook/tree/main/additional-databases/sagemaker

Updated docs to share sample lifecycle configuration file for use with SageMaker: https://github.com/aws/graph-notebook/tree/main/additional-databases/sagemaker

Hi @joywa (if you're still there) or anyone else. Is it necessary to generate the graph config in the lifecycle script?
Are these lines https://github.com/aws/graph-notebook/blob/e8d03645f6f532815db09bc06fcc0c83b907e663/additional-databases/sagemaker/sagemaker-notebook-lifecycle/install-graph-notebook-lc.sh#L76-L83
equivalent to running, for example, this in a notebook cell?:
%%graph_notebook_config
{
  "host": "your-neptune-endpoint",
  "neptune_service": "neptune-graph",
  "port": 443,
  "auth_mode": "IAM",
  "ssl": true,
  "ssl_verify": true,
  "aws_region": "your-neptune-region"
}

I would prefer not to hard-code my (Neptune Analytics) graph into the lifecycle configuration script, since I expect to delete the graph after using the notebook.

@rossjohnstone-paypay yes, you certainly can use %%graph_notebook_config to manually set the connection configuration after the notebook is created. If generate_config is not run as part of the lifecycle, the initial configuration will be populated with placeholder values, which can be overridden.

Hi @michaelnchin thanks. Would you be able to share a version of the lifecycle configuration script for use in JupyterLab within SageMaker Studio?
I tried simply executing the commands here but I'm not sure if I'm enabling the extensions within the correct instance of JupyterLab.

@rossjohnstone-paypay I believe SageMaker Studio uses JupyterLab 4 - graph-notebook currently supports up to JupyterLab 3, so it would not be compatible at the moment.
Related issue: https://github.com/aws/graph-notebook/issues/689


Wrapper for asym. crypto around nacl/box

This PR implements functionality for asymmetric encryption and decryption based on the currently used certificates. This will be required for the first order DRKey exchange.

This change is

Review status: 0 of 1 files reviewed at latest revision, all discussions resolved, some commit checks failed.

go/lib/crypto/asym.go, line 35 at r1 (raw file):

	UnsupportedSignAlgo        = "Unsupported signing algorithm"
	InvalidSignature           = "Invalid signature"
	FailedToGenerateKeyPairs   = "Failed to generate key pairs"

We usually use "Unable" in the code base.
replace with UnableToGenerateKeyPair =  "Unable to generate key pair"
(also, singular form)

go/lib/crypto/asym.go, line 39 at r1 (raw file):

	FailedToDecrypt            = "Failed to decrypt message"
	UnsupportedEncAlgo         = "Unsupported encryption algorithm"
	UnsupportedDecAlgo         = "Unsupported decryption algorithm"

Unused constant.
I would just remove it.

go/lib/crypto/asym.go, line 75 at r1 (raw file):

}

// GenKeyPairs generates a public/private key pair

The convention is to place . after these kinds of comments.
Also, move function to top.

go/lib/crypto/asym.go, line 76 at r1 (raw file):

// GenKeyPairs generates a public/private key pair
func GenKeyPairs(keygenAlgo string) (common.RawBytes, common.RawBytes, error) {

keygenAlgo is an odd name.
Maybe just algo?

go/lib/crypto/asym.go, line 98 at r1 (raw file):

// GenNonce takes an input length and returns a random nonce of the given length
func GenNonce(len uint16) (common.RawBytes, error) {

Any particular reason len is uint16 and not int?
Name should probably just be Nonce.

go/lib/crypto/asym.go, line 100 at r1 (raw file):

func GenNonce(len uint16) (common.RawBytes, error) {
	nonce := make([]byte, len)
	_, err := io.ReadFull(rand.Reader, nonce[:])

drop [:]

go/lib/crypto/asym.go, line 113 at r1 (raw file):

	switch strings.ToLower(algo) {
	case Curve25519xSalsa20Poly1305:
		if len(nonce) != 24 {

make this and all other magic numbers a constant.

go/lib/crypto/asym.go, line 120 at r1 (raw file):

		}
		// 192 bits of randomness should provide a sufficiently small probability of repeats.
		var nc *[24]byte

This will not allocate the array and segfault later on.
var nc [24]byte and pass &nc to box.Seal.

go/lib/crypto/asym.go, line 122 at r1 (raw file):

		var nc *[24]byte
		copy(nc[:], nonce)
		var pubk, privk *[32]byte

same as above.
Naming is somewhat hard to read.
Maybe pubKeyRaw, privKeyRaw, nonceRaw?

go/lib/crypto/asym.go, line 123 at r1 (raw file):

		copy(nc[:], nonce)
		var pubk, privk *[32]byte
		copy(pubk[:], pubkey[:32])

drop [:32]

go/lib/crypto/asym.go, line 143 at r1 (raw file):

		var nc [24]byte
		copy(nc[:], nonce[:24])
		var pubk, privk *[32]byte

same as above

Comments from Reviewable

Review status: 0 of 1 files reviewed at latest revision, 11 unresolved discussions.

go/lib/crypto/asym.go, line 35 at r1 (raw file):
Previously, Oncilla wrote…
We usually use "Unable" in the code base.
replace with UnableToGenerateKeyPair =  "Unable to generate key pair"
(also, singular form)

Ok. I'll keep that in mind.

go/lib/crypto/asym.go, line 39 at r1 (raw file):
Previously, Oncilla wrote…
Unused constant.
I would just remove it.

This is (now) used in the Decrypt function

go/lib/crypto/asym.go, line 75 at r1 (raw file):
Previously, Oncilla wrote…
The convention is to place . after these kinds of comments.
Also, move function to top.

Done.

go/lib/crypto/asym.go, line 76 at r1 (raw file):
Previously, Oncilla wrote…
keygenAlgo is an odd name.
Maybe just algo?

Done.

go/lib/crypto/asym.go, line 98 at r1 (raw file):
Previously, Oncilla wrote…
Any particular reason len is uint16 and not int?
Name should probably just be Nonce.

Done.

go/lib/crypto/asym.go, line 100 at r1 (raw file):
Previously, Oncilla wrote…
drop [:]

Done.

go/lib/crypto/asym.go, line 113 at r1 (raw file):
Previously, Oncilla wrote…
make this and all other magic numbers a constant.

Done.

go/lib/crypto/asym.go, line 120 at r1 (raw file):
Previously, Oncilla wrote…
This will not allocate the array and segfault later on.
var nc [24]byte and pass &nc to box.Seal.

Done.

go/lib/crypto/asym.go, line 122 at r1 (raw file):
Previously, Oncilla wrote…
same as above.
Naming is somewhat hard to read.
Maybe pubKeyRaw, privKeyRaw, nonceRaw?

Done.

go/lib/crypto/asym.go, line 123 at r1 (raw file):
Previously, Oncilla wrote…
drop [:32]

Done.

go/lib/crypto/asym.go, line 143 at r1 (raw file):
Previously, Oncilla wrote…
same as above

Done.

Comments from Reviewable

Review status: all files reviewed at latest revision, 2 unresolved discussions, some commit checks failed.

go/lib/crypto/asym.go, line 39 at r1 (raw file):
Previously, brothen wrote…
This is (now) used in the Decrypt function

I would rather have just the UnsupportedEncAlgo string.

go/lib/crypto/asym.go, line 113 at r1 (raw file):
Previously, brothen wrote…
Done.

Name should be a bit more specific.
E.g. pubKeySize of Ed25519 is 64 byte and not 32 byte.

Comments from Reviewable

go/lib/crypto/asym.go, line 34 at r2 (raw file):

	Ed25519                    = "ed25519"
	Curve25519xSalsa20Poly1305 = "curve25519xsalsa20poly1305"

add blank line to separate const blocks.

Comments from Reviewable

Review status: 0 of 1 files reviewed at latest revision, 3 unresolved discussions, some commit checks failed.

go/lib/crypto/asym.go, line 39 at r1 (raw file):
Previously, Oncilla wrote…
I would rather have just the UnsupportedEncAlgo string.

Ok. I will remove it.

go/lib/crypto/asym.go, line 113 at r1 (raw file):
Previously, Oncilla wrote…
Name should be a bit more specific.
E.g. pubKeySize of Ed25519 is 64 byte and not 32 byte.

Done.

go/lib/crypto/asym.go, line 34 at r2 (raw file):
Previously, Oncilla wrote…
add blank line to separate const blocks.

Done.

Comments from Reviewable

Reviewed 1 of 1 files at r3.
Review status: all files reviewed at latest revision, all discussions resolved, some commit checks failed.

Comments from Reviewable

Review status: 0 of 2 files reviewed, 3 unresolved discussions (waiting on @Oncilla and @brothen)

go/lib/crypto/asym.go, line 1 at r4 (raw file):

// Copyright 2018 ETH Zurich

undo

go/lib/crypto/asym_test.go, line 32 at r4 (raw file):

		0x7d, 0xb1, 0x26, 0xd8, 0x89, 0xf6, 0xda, 0xdd}
	Ed25519TestPublicKey = common.RawBytes{0x77, 0xf4, 0x8b, 0x59, 0xca, 0xed, 0xa7, 0x77, 0x51,
		0xed, 0x13,

odd formatting

go/lib/crypto/asym_test.go, line 52 at r4 (raw file):

		0xef, 0x7b, 0x9b, 0xcc, 0x3c, 0x40, 0xc0, 0xff, 0x75, 0x09}

	// NaClBox test vectors

These test vectors are unused
Add some tests for NaClBox

Comments from Reviewable

Review status: 0 of 2 files reviewed, 4 unresolved discussions (waiting on @Oncilla and @brothen)

go/lib/crypto/asym_test.go, line 87 at r4 (raw file):

	// multiple signing operations with the same key more efficient...""
	Convey("Sign should sign message correctly", t, func() {
		sig, err := Sign(Ed25519TestMsg, append(Ed25519TestPrivateKey, Ed25519TestPublicKey...), "Ed25519")

Since #1604 is merged, use ed22519.NewKeyFromSeed instead.

Comments from Reviewable

Review status: 0 of 2 files reviewed, 4 unresolved discussions (waiting on @Oncilla and @brothen)

go/lib/crypto/asym.go, line 1 at r4 (raw file):
Previously, Oncilla wrote…
undo

Done.

go/lib/crypto/asym_test.go, line 32 at r4 (raw file):
Previously, Oncilla wrote…
odd formatting

Done.

go/lib/crypto/asym_test.go, line 52 at r4 (raw file):
Previously, Oncilla wrote…
These test vectors are unused
Add some tests for NaClBox

Done.

go/lib/crypto/asym_test.go, line 87 at r4 (raw file):
Previously, Oncilla wrote…
Since #1604 is merged, use ed22519.NewKeyFromSeed instead.

I would prefer to keep the current testcase as it is also included in the python

Comments from Reviewable

Review status: 0 of 2 files reviewed, 6 unresolved discussions (waiting on @Oncilla and @brothen)

go/lib/crypto/asym.go, line 46 at r5 (raw file):
Previously, Oncilla wrote…
A wild constant appears.
As discussed before, just remove it.

Done.

go/lib/crypto/asym_test.go, line 87 at r4 (raw file):
Previously, Oncilla wrote…
Right. I'm talking about replacing it with ed25519.NewKeyFromSeed(Ed25519TestPrivateKey).
The test case stays the same.
In any case: Line length.

Done.

go/lib/crypto/asym_test.go, line 53 at r5 (raw file):
Previously, Oncilla wrote…
Line length

Done.

go/lib/crypto/asym_test.go, line 125 at r5 (raw file):
Previously, Oncilla wrote…
Line length.

Done.

go/lib/crypto/asym_test.go, line 130 at r5 (raw file):
Previously, Oncilla wrote…
line length

Done.

go/lib/crypto/asym_test.go, line 158 at r5 (raw file):
Previously, Oncilla wrote…
I like this randomness check :100:  ;)

:1st_place_medal:

Comments from Reviewable

Reviewed 2 of 2 files at r6.
Review status: :shipit: complete! all files reviewed, all discussions resolved

Comments from Reviewable


Update specs2-matcher-extra to 4.11.0

Updates org.specs2:specs2-matcher-extra from 4.8.3 to 4.11.0.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.specs2", artifactId = "specs2-matcher-extra" } ]

labels: test-library-update, semver-minor

Superseded by #23.


Port over external CSP3 hash support

Hi,
I needed this so I tried to port over the original PR by @sersorrel from https://github.com/slackhq/csp-html-webpack-plugin/pull/87. Apart from adding the support for hashing external scripts I also changed the way jest tests are run: if they fail, jest would go into timeout since done() was never called. Instead I moved it over to Promises, so fails are fast.
All tests are green with this but I haven't tried it out in practice.
This should fix #74

OK let me know when its ready and I will push 6.0.5 to NPM

This is not actually working for non-online scripts. The webpack hooks when emitting JS files or other assets don't get called. I'm not sure I'll have the time to look into this because we'll probably move to using nonces instead of hashes.

No worries lets leave this draft open for others to see in the future.


move quo to its own module

Fixes #104
Also makes the output less spammy
cc @LinuxMercedes

Leaving a do-not-merge label on until I actually test it at least once.

This looks good to me. It would be cool if we didn't have to add new modules manually to quo, but that would require an implementation of #3--and how often do we add new quote modules anyway?

There was that one time we had blerg.....
Anyways, all manually tested now, things seem to be fine.


Check GA & nginx logs to see how often Staging is accessed from external/non-Heidelberg IP addresses

Closing this - low priority and unlikely to ever leave the backlog


Add option to bulk send multiple ordinals at once

Instead of clicking a single ordinal, perhaps there can be an option to select multiple and then click send. Should it even allow sending stamps and ordinals in a single transaction?

Curious about the user scenarios that require this?

Curious about the user scenarios that require this?

The user minted a collection to their address and now want to send them to winners and/or community members.

Users who want to migrate to another address/wallet.

To save on fees by sending them in a single transaction.

@fabric-8 something to keep in mind while incorporating collectibles into the standard send flow – we'll want the ability to send multiple at once


Failure in building MLIR dialects and utilities from source

1. System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 22.04.3 LTS
TensorFlow installation (pip package or built from source): build from source
TensorFlow library (version, if pip package or github SHA, if built from source):  commit id 2454fa808a6

2. Code
Provide code to help us reproduce your issues using one of the following options:
Option A: Reference colab notebooks

Reference TensorFlow Model Colab: Demonstrate how to build your TF model.
Reference TensorFlow Lite Model Colab: Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.

Option B: Paste your code here or provide a link to a custom end-to-end colab
$ bazel build  -j tensorflow/compiler/mlir/...
...
ERROR: /home/.../tensorflow/tensorflow/core/tfrt/graph_executor/BUILD:27:11: Compiling tensorflow/core/tfrt/graph_executor/graph_execution_options.cc failed: (Exit 1): clang failed: error executing command (from target //tensorflow/core/tfrt/graph_executor:graph_execution_options) /usr/lib/llvm-14/bin/clang -U_FORTIFY_SOURCE -fstack-protector -Wall -Wthread-safety -Wself-assign -Wunused-but-set-parameter -Wno-free-nonheap-object -fcolor-diagnostics -fno-omit-frame-pointer -g0 ... (remaining 241 arguments skipped)
In file included from tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:19:
external/com_google_absl/absl/log/log.h:199:9: warning: 'LOG' macro redefined [-Wmacro-redefined]
#define LOG(severity) ABSL_LOG_INTERNAL_LOG_IMPL(_##severity)
        ^
external/local_tsl/tsl/platform/default/logging.h:165:9: note: previous definition is here
#define LOG(severity) _TF_LOG_##severity
        ^
In file included from tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:19:
external/com_google_absl/absl/log/log.h:237:9: warning: 'LOG_EVERY_N' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_N(severity, n) \
        ^
external/local_tsl/tsl/platform/default/logging.h:278:9: note: previous definition is here
#define LOG_EVERY_N(severity, n)                       \
        ^
In file included from tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:19:
external/com_google_absl/absl/log/log.h:245:9: warning: 'LOG_FIRST_N' macro redefined [-Wmacro-redefined]
#define LOG_FIRST_N(severity, n) \
        ^
external/local_tsl/tsl/platform/default/logging.h:284:9: note: previous definition is here
#define LOG_FIRST_N(severity, n)                       \
        ^
In file included from tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:19:
external/com_google_absl/absl/log/log.h:253:9: warning: 'LOG_EVERY_POW_2' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_POW_2(severity) \
        ^
external/local_tsl/tsl/platform/default/logging.h:290:9: note: previous definition is here
#define LOG_EVERY_POW_2(severity)                         \
        ^
In file included from tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:19:
external/com_google_absl/absl/log/log.h:265:9: warning: 'LOG_EVERY_N_SEC' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_N_SEC(severity, n_seconds) \
        ^
external/local_tsl/tsl/platform/default/logging.h:300:9: note: previous definition is here
#define LOG_EVERY_N_SEC(severity, n_seconds)                      \
        ^
tensorflow/core/tfrt/graph_executor/graph_execution_options.cc:131:16: error: no matching function for call to 'StrCat'
            << absl::StrCat(options.model_metadata)
               ^~~~~~~~~~~~
external/com_google_absl/absl/strings/str_cat.h:451:41: note: candidate function not viable: no known conversion from 'const tensorflow::SessionMetadata' to 'const absl::AlphaNum' for 1st argument
ABSL_MUST_USE_RESULT inline std::string StrCat(const AlphaNum& a) {
                                        ^
external/com_google_absl/absl/strings/str_cat.h:449:41: note: candidate function not viable: requires 0 arguments, but 1 was provided
ABSL_MUST_USE_RESULT inline std::string StrCat() { return std::string(); }
                                        ^
external/com_google_absl/absl/strings/str_cat.h:455:34: note: candidate function not viable: requires 2 arguments, but 1 was provided
ABSL_MUST_USE_RESULT std::string StrCat(const AlphaNum& a, const AlphaNum& b);
                                 ^
external/com_google_absl/absl/strings/str_cat.h:456:34: note: candidate function not viable: requires 3 arguments, but 1 was provided
ABSL_MUST_USE_RESULT std::string StrCat(const AlphaNum& a, const AlphaNum& b,
                                 ^
external/com_google_absl/absl/strings/str_cat.h:458:34: note: candidate function not viable: requires 4 arguments, but 1 was provided
ABSL_MUST_USE_RESULT std::string StrCat(const AlphaNum& a, const AlphaNum& b,
                                 ^
external/com_google_absl/absl/strings/str_cat.h:463:41: note: candidate function template not viable: requires at least 5 arguments, but 1 was provided
ABSL_MUST_USE_RESULT inline std::string StrCat(
                                        ^
5 warnings and 1 error generated.
INFO: Elapsed time: 27.129s, Critical Path: 24.43s
INFO: 1098 processes: 701 internal, 397 local.
FAILED: Build did NOT complete successfully

3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:

Model produces wrong results and/or has lesser accuracy.
Model produces correct results, but it is slower than expected.

4. (optional) RNN conversion support
If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.
5. (optional) Any other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

@wonjeon Could you try cleaning the build directory with cmake --build . --target clean and then rebuilding with cmake --build , please make sure that you have installed all compatible configurations correctly with the latest build. Thank you!

Do you have any resolution for bazel? I don't use cmake for this process.

Hi @wonjeon,
The build failure might be due to  StrCat  function in graph_execution_options.cc.  A recent commit  afc843c related to this function in github repo is updated. Could you please try with this commit for your usecase and let us know  the status.
Thank You.

Hi @LakshmiKalaKadali ,
Tried the latest code including the commit that you mentioned, but it still doesn't compile the code correctly. I'm using clang 14.0.0-1ubuntu1.1 and python 3.10.12.
$ bazel build -j 24 tensorflow/compiler/mlir/...
...

ERROR: /home/wonjeo01/tensorflow/tensorflow/compiler/mlir/tfrt/transforms/ifrt/BUILD:88:11: Compiling tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc failed: (Exit 1): clang failed: error executing command (from target //tensorflow/compiler/mlir/tfrt/transforms/ifrt:tf2hlo) /usr/lib/llvm-14/bin/clang -U_FORTIFY_SOURCE -fstack-protector -Wall -Wthread-safety -Wself-assign -Wunused-but-set-parameter -Wno-free-nonheap-object -fcolor-diagnostics -fno-omit-frame-pointer -g0 ... (remaining 486 arguments skipped)
In file included from tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:24:
external/com_google_absl/absl/log/log.h:199:9: warning: 'LOG' macro redefined [-Wmacro-redefined]
#define LOG(severity) ABSL_LOG_INTERNAL_LOG_IMPL(_##severity)
        ^
external/local_tsl/tsl/platform/default/logging.h:165:9: note: previous definition is here
#define LOG(severity) _TF_LOG_##severity
        ^
In file included from tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:24:
external/com_google_absl/absl/log/log.h:237:9: warning: 'LOG_EVERY_N' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_N(severity, n) \
        ^
external/local_tsl/tsl/platform/default/logging.h:278:9: note: previous definition is here
#define LOG_EVERY_N(severity, n)                       \
        ^
In file included from tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:24:
external/com_google_absl/absl/log/log.h:245:9: warning: 'LOG_FIRST_N' macro redefined [-Wmacro-redefined]
#define LOG_FIRST_N(severity, n) \
        ^
external/local_tsl/tsl/platform/default/logging.h:284:9: note: previous definition is here
#define LOG_FIRST_N(severity, n)                       \
        ^
In file included from tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:24:
external/com_google_absl/absl/log/log.h:253:9: warning: 'LOG_EVERY_POW_2' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_POW_2(severity) \
        ^
external/local_tsl/tsl/platform/default/logging.h:290:9: note: previous definition is here
#define LOG_EVERY_POW_2(severity)                         \
        ^
In file included from tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:24:
external/com_google_absl/absl/log/log.h:265:9: warning: 'LOG_EVERY_N_SEC' macro redefined [-Wmacro-redefined]
#define LOG_EVERY_N_SEC(severity, n_seconds) \
        ^
external/local_tsl/tsl/platform/default/logging.h:300:9: note: previous definition is here
#define LOG_EVERY_N_SEC(severity, n_seconds)                      \
        ^
tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:83:35: error: no viable conversion from '::llvm::StringRef' to 'const std::string' (aka 'const basic_string<char>')
    if (!metadata.ParseFromString(metadata_attr.getValue())) {
                                  ^~~~~~~~~~~~~~~~~~~~~~~~
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:456:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'const std::basic_string<char> &' for 1st argument
      basic_string(const basic_string& __str)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:533:7: note: candidate constructor template not viable: no known conversion from '::llvm::StringRef' to 'const char *' for 1st argument
      basic_string(const _CharT* __s, const _Alloc& __a = _Alloc())
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:565:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'std::basic_string<char> &&' for 1st argument
      basic_string(basic_string&& __str) noexcept
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:592:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'initializer_list<char>' for 1st argument
      basic_string(initializer_list<_CharT> __l, const _Alloc& __a = _Alloc())
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:448:7: note: explicit constructor is not a candidate
      basic_string(const _Alloc& __a) _GLIBCXX_NOEXCEPT
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:664:2: note: explicit constructor is not a candidate
        basic_string(const _Tp& __t, const _Alloc& __a = _Alloc())
        ^
external/llvm-project/llvm/include/llvm/ADT/StringRef.h:248:15: note: candidate function
    constexpr operator std::string_view() const {
              ^
external/com_google_protobuf/src/google/protobuf/message_lite.h:280:74: note: passing argument to parameter 'data' here
  PROTOBUF_ATTRIBUTE_REINITIALIZES bool ParseFromString(ConstStringParam data);
                                                                         ^
tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:94:13: error: no viable conversion from '::llvm::StringRef' to 'const std::string' (aka 'const basic_string<char>')
            metadata_text_attr.getValue(), &metadata)) {
            ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:456:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'const std::basic_string<char> &' for 1st argument
      basic_string(const basic_string& __str)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:533:7: note: candidate constructor template not viable: no known conversion from '::llvm::StringRef' to 'const char *' for 1st argument
      basic_string(const _CharT* __s, const _Alloc& __a = _Alloc())
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:565:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'std::basic_string<char> &&' for 1st argument
      basic_string(basic_string&& __str) noexcept
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:592:7: note: candidate constructor not viable: no known conversion from '::llvm::StringRef' to 'initializer_list<char>' for 1st argument
      basic_string(initializer_list<_CharT> __l, const _Alloc& __a = _Alloc())
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:448:7: note: explicit constructor is not a candidate
      basic_string(const _Alloc& __a) _GLIBCXX_NOEXCEPT
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:664:2: note: explicit constructor is not a candidate
        basic_string(const _Tp& __t, const _Alloc& __a = _Alloc())
        ^
external/llvm-project/llvm/include/llvm/ADT/StringRef.h:248:15: note: candidate function
    constexpr operator std::string_view() const {
              ^
external/com_google_protobuf/src/google/protobuf/text_format.h:479:48: note: passing argument to parameter 'input' here
  static bool ParseFromString(ConstStringParam input, Message* output);
                                               ^
tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:104:62: error: invalid operands to binary expression ('tsl::internal::LogMessage' and 'tensorflow::tpu::TPUCompileMetadataProto')
  VLOG(3) << "TpuCompileMetadata before shape is populated " << metadata;
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ^  ~~~~~~~~
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/cstddef:126:5: note: candidate function template not viable: no known conversion from 'tsl::internal::LogMessage' to 'std::byte' for 1st argument
    operator<<(byte __b, _IntegerType __shift) noexcept
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/system_error:279:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const std::error_code' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, const error_code& __e)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:518:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'char' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:524:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:530:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'signed char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, signed char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:535:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, unsigned char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:611:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:624:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const signed char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const signed char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:629:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const unsigned char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const unsigned char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/ostream.tcc:321:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const char *' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, const char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:79:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Resetiosflags' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Resetiosflags __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:109:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setiosflags' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setiosflags __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:143:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setbase' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setbase __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:208:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setprecision' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setprecision __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:238:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setw' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setw __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1020:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const std::bernoulli_distribution' for 2nd argument
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/thread:92:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'thread::id' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, thread::id __id)
    ^
./tensorflow/core/framework/tensor_shape.h:452:22: note: candidate function not viable: expects an lvalue for 1st argument
inline std::ostream& operator<<(std::ostream& os, const TensorShape& ts) {
                     ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:513:5: note: candidate template ignored: deduced conflicting types for parameter '_CharT' ('char' vs. 'tensorflow::tpu::TPUCompileMetadataProto')
    operator<<(basic_ostream<_CharT, _Traits>& __out, _CharT __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/string_view:667:5: note: candidate template ignored: could not match 'basic_string_view<_CharT, _Traits>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:6531:5: note: candidate template ignored: could not match 'basic_string<_CharT, _Traits, _Alloc>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:594:5: note: candidate template ignored: could not match 'const _CharT *' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __out, const _CharT* __s)
    ^
./tensorflow/core/framework/tensor_shape.h:346:15: note: candidate template ignored: could not match 'TensorShapeBase<Shape>' against 'tensorflow::tpu::TPUCompileMetadataProto'
std::ostream& operator<<(std::ostream& os, const TensorShapeBase<Shape>& tsb) {
              ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:750:5: note: candidate template ignored: substitution failure [with _Ostream = tsl::internal::LogMessage, _Tp = tensorflow::tpu::TPUCompileMetadataProto]: invalid operands to binary expression ('tsl::internal::LogMessage' and 'const tensorflow::tpu::TPUCompileMetadataProto')
    operator<<(_Ostream&& __os, const _Tp& __x)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/shared_ptr.h:70:5: note: candidate template ignored: could not match '__shared_ptr<_Tp, _Lp>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_Ch, _Tr>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:178:5: note: candidate template ignored: could not match '_Setfill<_CharT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setfill<_CharT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:311:5: note: candidate template ignored: could not match '_Put_money<_MoneyT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Put_money<_MoneyT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:363:5: note: candidate template ignored: could not match '_Put_time<_CharT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Put_time<_CharT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/complex:555:5: note: candidate template ignored: could not match 'complex<_Tp>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, const complex<_Tp>& __x)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bitset:1540:5: note: candidate template ignored: could not match 'bitset<_Nb>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.h:1309:5: note: candidate template ignored: could not match 'std::independent_bits_engine<_RandomNumberEngine, __w, _UIntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:154:5: note: candidate template ignored: could not match 'linear_congruential_engine<_UIntType, __a, __c, __m>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:474:5: note: candidate template ignored: could not match 'mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:628:5: note: candidate template ignored: could not match 'subtract_with_carry_engine<_UIntType, __w, __s, __r>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:696:5: note: candidate template ignored: could not match 'discard_block_engine<_RandomNumberEngine, __p, __r>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:857:5: note: candidate template ignored: could not match 'shuffle_order_engine<_RandomNumberEngine, __k>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:901:5: note: candidate template ignored: could not match 'uniform_int_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:959:5: note: candidate template ignored: could not match 'uniform_real_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1101:5: note: candidate template ignored: could not match 'geometric_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1215:5: note: candidate template ignored: could not match 'negative_binomial_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1425:5: note: candidate template ignored: could not match 'poisson_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1691:5: note: candidate template ignored: could not match 'binomial_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1753:5: note: candidate template ignored: could not match 'exponential_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1919:5: note: candidate template ignored: could not match 'normal_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1986:5: note: candidate template ignored: could not match 'lognormal_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2058:5: note: candidate template ignored: could not match 'chi_squared_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2144:5: note: candidate template ignored: could not match 'cauchy_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2219:5: note: candidate template ignored: could not match 'fisher_f_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2293:5: note: candidate template ignored: could not match 'student_t_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2462:5: note: candidate template ignored: could not match 'gamma_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2538:5: note: candidate template ignored: could not match 'weibull_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2612:5: note: candidate template ignored: could not match 'extreme_value_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2748:5: note: candidate template ignored: could not match 'discrete_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2970:5: note: candidate template ignored: could not match 'piecewise_constant_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:3176:5: note: candidate template ignored: could not match 'piecewise_linear_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:108:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__ostream_type &(*)(std::basic_ostream<char>::__ostream_type &)' (aka 'basic_ostream<char, std::char_traits<char>> &(*)(basic_ostream<char, std::char_traits<char>> &)') for 1st argument
      operator<<(__ostream_type& (*__pf)(__ostream_type&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:117:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__ios_type &(*)(std::basic_ostream<char>::__ios_type &)' (aka 'basic_ios<char, std::char_traits<char>> &(*)(basic_ios<char, std::char_traits<char>> &)') for 1st argument
      operator<<(__ios_type& (*__pf)(__ios_type&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:127:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::ios_base &(*)(std::ios_base &)' for 1st argument
      operator<<(ios_base& (*__pf) (ios_base&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:166:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long' for 1st argument
      operator<<(long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:170:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned long' for 1st argument
      operator<<(unsigned long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:174:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'bool' for 1st argument
      operator<<(bool __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:178:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'short' for 1st argument
      operator<<(short __n);
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:181:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned short' for 1st argument
      operator<<(unsigned short __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:189:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'int' for 1st argument
      operator<<(int __n);
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:192:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned int' for 1st argument
      operator<<(unsigned int __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:201:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long long' for 1st argument
      operator<<(long long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:205:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned long long' for 1st argument
      operator<<(unsigned long long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:220:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'double' for 1st argument
      operator<<(double __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:224:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'float' for 1st argument
      operator<<(float __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:232:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long double' for 1st argument
      operator<<(long double __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:245:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const void *' for 1st argument; take the address of the argument with &
      operator<<(const void* __p)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:250:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::nullptr_t' for 1st argument
      operator<<(nullptr_t)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:283:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__streambuf_type *' (aka 'basic_streambuf<char, std::char_traits<char>> *') for 1st argument
      operator<<(__streambuf_type* __sb);
      ^
tensorflow/compiler/mlir/tfrt/transforms/ifrt/tf2hlo.cc:191:39: error: invalid operands to binary expression ('tsl::internal::LogMessage' and 'tensorflow::tpu::TPUCompileMetadataProto')
  VLOG(1) << "Compilation metadata: " << compile_metadata;
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ^  ~~~~~~~~~~~~~~~~
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/cstddef:126:5: note: candidate function template not viable: no known conversion from 'tsl::internal::LogMessage' to 'std::byte' for 1st argument
    operator<<(byte __b, _IntegerType __shift) noexcept
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/system_error:279:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const std::error_code' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, const error_code& __e)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:518:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'char' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:524:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:530:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'signed char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, signed char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:535:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned char' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, unsigned char __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:611:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:624:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const signed char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const signed char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:629:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const unsigned char *' for 2nd argument
    operator<<(basic_ostream<char, _Traits>& __out, const unsigned char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/ostream.tcc:321:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const char *' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, const char* __s)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:79:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Resetiosflags' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Resetiosflags __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:109:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setiosflags' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setiosflags __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:143:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setbase' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setbase __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:208:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setprecision' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setprecision __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:238:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::_Setw' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setw __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1020:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const std::bernoulli_distribution' for 2nd argument
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/thread:92:5: note: candidate function template not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'thread::id' for 2nd argument
    operator<<(basic_ostream<_CharT, _Traits>& __out, thread::id __id)
    ^
./tensorflow/core/framework/tensor_shape.h:452:22: note: candidate function not viable: expects an lvalue for 1st argument
inline std::ostream& operator<<(std::ostream& os, const TensorShape& ts) {
                     ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:513:5: note: candidate template ignored: deduced conflicting types for parameter '_CharT' ('char' vs. 'tensorflow::tpu::TPUCompileMetadataProto')
    operator<<(basic_ostream<_CharT, _Traits>& __out, _CharT __c)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/string_view:667:5: note: candidate template ignored: could not match 'basic_string_view<_CharT, _Traits>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/basic_string.h:6531:5: note: candidate template ignored: could not match 'basic_string<_CharT, _Traits, _Alloc>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:594:5: note: candidate template ignored: could not match 'const _CharT *' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __out, const _CharT* __s)
    ^
./tensorflow/core/framework/tensor_shape.h:346:15: note: candidate template ignored: could not match 'TensorShapeBase<Shape>' against 'tensorflow::tpu::TPUCompileMetadataProto'
std::ostream& operator<<(std::ostream& os, const TensorShapeBase<Shape>& tsb) {
              ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:750:5: note: candidate template ignored: substitution failure [with _Ostream = tsl::internal::LogMessage, _Tp = tensorflow::tpu::TPUCompileMetadataProto]: invalid operands to binary expression ('tsl::internal::LogMessage' and 'const tensorflow::tpu::TPUCompileMetadataProto')
    operator<<(_Ostream&& __os, const _Tp& __x)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/shared_ptr.h:70:5: note: candidate template ignored: could not match '__shared_ptr<_Tp, _Lp>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_Ch, _Tr>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:178:5: note: candidate template ignored: could not match '_Setfill<_CharT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Setfill<_CharT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:311:5: note: candidate template ignored: could not match '_Put_money<_MoneyT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Put_money<_MoneyT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/iomanip:363:5: note: candidate template ignored: could not match '_Put_time<_CharT>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, _Put_time<_CharT> __f)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/complex:555:5: note: candidate template ignored: could not match 'complex<_Tp>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(basic_ostream<_CharT, _Traits>& __os, const complex<_Tp>& __x)
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bitset:1540:5: note: candidate template ignored: could not match 'bitset<_Nb>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.h:1309:5: note: candidate template ignored: could not match 'std::independent_bits_engine<_RandomNumberEngine, __w, _UIntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:154:5: note: candidate template ignored: could not match 'linear_congruential_engine<_UIntType, __a, __c, __m>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:474:5: note: candidate template ignored: could not match 'mersenne_twister_engine<_UIntType, __w, __n, __m, __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:628:5: note: candidate template ignored: could not match 'subtract_with_carry_engine<_UIntType, __w, __s, __r>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:696:5: note: candidate template ignored: could not match 'discard_block_engine<_RandomNumberEngine, __p, __r>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:857:5: note: candidate template ignored: could not match 'shuffle_order_engine<_RandomNumberEngine, __k>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:901:5: note: candidate template ignored: could not match 'uniform_int_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:959:5: note: candidate template ignored: could not match 'uniform_real_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1101:5: note: candidate template ignored: could not match 'geometric_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1215:5: note: candidate template ignored: could not match 'negative_binomial_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1425:5: note: candidate template ignored: could not match 'poisson_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1691:5: note: candidate template ignored: could not match 'binomial_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1753:5: note: candidate template ignored: could not match 'exponential_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1919:5: note: candidate template ignored: could not match 'normal_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:1986:5: note: candidate template ignored: could not match 'lognormal_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2058:5: note: candidate template ignored: could not match 'chi_squared_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2144:5: note: candidate template ignored: could not match 'cauchy_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2219:5: note: candidate template ignored: could not match 'fisher_f_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2293:5: note: candidate template ignored: could not match 'student_t_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2462:5: note: candidate template ignored: could not match 'gamma_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2538:5: note: candidate template ignored: could not match 'weibull_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2612:5: note: candidate template ignored: could not match 'extreme_value_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2748:5: note: candidate template ignored: could not match 'discrete_distribution<_IntType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:2970:5: note: candidate template ignored: could not match 'piecewise_constant_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/bits/random.tcc:3176:5: note: candidate template ignored: could not match 'piecewise_linear_distribution<_RealType>' against 'tensorflow::tpu::TPUCompileMetadataProto'
    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
    ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:108:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__ostream_type &(*)(std::basic_ostream<char>::__ostream_type &)' (aka 'basic_ostream<char, std::char_traits<char>> &(*)(basic_ostream<char, std::char_traits<char>> &)') for 1st argument
      operator<<(__ostream_type& (*__pf)(__ostream_type&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:117:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__ios_type &(*)(std::basic_ostream<char>::__ios_type &)' (aka 'basic_ios<char, std::char_traits<char>> &(*)(basic_ios<char, std::char_traits<char>> &)') for 1st argument
      operator<<(__ios_type& (*__pf)(__ios_type&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:127:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::ios_base &(*)(std::ios_base &)' for 1st argument
      operator<<(ios_base& (*__pf) (ios_base&))
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:166:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long' for 1st argument
      operator<<(long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:170:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned long' for 1st argument
      operator<<(unsigned long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:174:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'bool' for 1st argument
      operator<<(bool __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:178:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'short' for 1st argument
      operator<<(short __n);
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:181:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned short' for 1st argument
      operator<<(unsigned short __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:189:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'int' for 1st argument
      operator<<(int __n);
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:192:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned int' for 1st argument
      operator<<(unsigned int __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:201:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long long' for 1st argument
      operator<<(long long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:205:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'unsigned long long' for 1st argument
      operator<<(unsigned long long __n)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:220:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'double' for 1st argument
      operator<<(double __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:224:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'float' for 1st argument
      operator<<(float __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:232:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'long double' for 1st argument
      operator<<(long double __f)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:245:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'const void *' for 1st argument; take the address of the argument with &
      operator<<(const void* __p)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:250:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::nullptr_t' for 1st argument
      operator<<(nullptr_t)
      ^
/usr/lib/gcc/x86_64-linux-gnu/11/../../../../include/c++/11/ostream:283:7: note: candidate function not viable: no known conversion from 'tensorflow::tpu::TPUCompileMetadataProto' to 'std::basic_ostream<char>::__streambuf_type *' (aka 'basic_streambuf<char, std::char_traits<char>> *') for 1st argument
      operator<<(__streambuf_type* __sb);
      ^
5 warnings and 4 errors generated.

Hi @wonjeon, can you ensure your system is updated to a tested build configuration for your system: https://www.tensorflow.org/install/source#tested_build_configurations specifically it seems your Clang is out of date (we tested against 16.0). Also what does ubuntu1.1 mean? Reason being I don't usually see Ubuntu versions that aren't 22.XX LTS, 20.XX LTS, 18.XX LTS etc. Thanks for your help.


Complete deployment deletion of AccessPolicy resources

The docs say that keyvault accesspolicies are not affected by complete mode deletion. If I redeploy a keyvault without accesspolicies all the before existing accesspolicies are gone. Is the documentation not up to date or is this an ARM issue?

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 39a7b827-35ff-060d-55ea-591d6d168025
Version Independent ID: 506704c2-309f-cff4-6c75-ad42d44a7dfb
Content: Complete mode deletion - Azure Resource Manager
Content Source: articles/azure-resource-manager/templates/deployment-complete-mode-deletion.md
Service: azure-resource-manager
Sub-service: templates
GitHub Login: @mumian
Microsoft Alias: jgao

@joerg996 Thanks for your comment. We will review the issue and get back to you shortly.

@joerg996 - It looks like accesspolicies is both a property on the keyvault and a separate resource type. Was your existing accesspolicies implemented as a separate resource?

I ran a test and noticed that even if a deploy accesspolicies as a separate resource, it gets added to the array property on the keyvault. So, redeploying that keyvault without the same accesspolicies would be interpreted as an update. I'll update the docs to reflect this case.

@tfitzmac I deployed accesspolicies as a resource.

Thanks for the information. I have updated the article. It should get published later today.
#please-close


wai-middleware-static-embedded is on hackage

wai-middleware-static-embedded is on hackage: we can remove the local copy and use that package.

https://hackage.haskell.org/package/wai-middleware-static-embedded-<IP_ADDRESS>#readme


adding image quality assessment process name

Including image quality assessment process name. I will be mainly using this as metadata to evaluate image stitching transformations and using no-reference image quality metrics for smartspim datasets. This is a new capsule that will be included in the pipeline.

I think we want a generic quality control process name and not something this granular


Created a Program for Boundary Traversal of Binary Tree

Great work @iamkarn007 please give this repo a star if it really helped you to complete your PR.
Also follow me for follow back if you want to get connected with me for any such open source contribution program. Thank you 😊


Feat/improve api

So now we actually retrieve the signature from the document itself, since it is required for verification.
Also adding:

nodejs code as part of the build
renaming package to match the one published on npm
fixing a promise race misbehaviour introduced by zealous linting

:tada: This PR is included in version 1.0.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Specifically which browser versions are supported?

I notice that firefox 4 to 10 do not work for a number of the examples in the examples page.
e.g. http://vuejs.org/examples/grid-component.html
The following is a link to the screenshots produced for those versions:
https://www.browserstack.com/screenshots/16186472da07af3c3696983908409a843f325bf4
The site seems to indicate that ECMAScript 5+ is required, but my understanding is that firefox 4+ has implemented nearly all of that.
The Galaxy S2 and Galaxy Note (original) seem to show nothing at all for that example page, but maybe the browser used is pre ECMAScript 5.
Is there a formal list of what browsers are supported?
(I know all the browsers and devices I have mentioned are quite old, so no problem if not supporting, I would just like to know).
Thanks,
Andrew

Hmm, don't really have a comprehensive list for all the legacy ones...
For Firefox - since it auto-upgrades since version 16, support for any version before that cannot be guaranteed.
For Android - every release is tested against an Android 4.2 browser, but versions before that cannot be guaranteed.

Thanks for the answer Evan.


Regression? wikipush: TypeError("argument of type 'NoneType' is not iterable")

wikipush -s or -t ormk -q "[[isA::Event series]]"
wikipush: TypeError("argument of type 'NoneType' is not iterable")

I traced down the issue and the Type error comes from an incorrect handling of empty query results. I fixed this issue but found another one #55


Missing data

Problem
One of the datasets in X-ray Computed Tomography Reconstructions of Partially Saturated Vegetated Sand seems to be missing. Specifically, the one labeled as FineSand_Day2Growth.tif, whose links sends to a 404 page.
Solution
We have contact with the owners of that dataset.

Fixed 59ecf8196b67107a2302d33523432279a37475f5


Improve process around changing build definitions

Use this issue as an opportunity to setup new Notebook-based documentation.

TODO: make a Jupyter book to organize the processes.


What prevents restricted token holder from using it’s proof token instead ?

I assumed that proofs would be distinguishable from a tokens via extra signature or something so that derived token holder could not simply pull out more capable proof in to escalate privileges. However I can’t see evidence of that in the implementation and spec also seems to suggest that:

Inline proofs MUST include the entire encoded token, since they will be validated by the receiver.
From: https://whitepaper.fission.codes/access-control/ucan/jwt-authentication

Tests in the repo also seem to suggest the same
https://github.com/ucan-wg/ucan/blob/bfbdbdac3cd7cd58d0382c683d2843a536e1eb9d/tests/token.test.ts#L57-L69
I may be misunderstanding something and if so it is probably a good idea to update language to communicate this more clearly.

You need to sign a UCAN to the service that you're making a request to. You'd need the root key in order to do that.

Just flagging that all of this kind of thing (end to end flows, helper functions, &c) needs to end up in the formal spec that will be in this GH org... "soon"

Thank you for raising it 🙏

(This got answered above, and confirmed in Discord. TL;DR this needs to be made clearer in prose, and ideally with helpers in the library's API)

@expede I was just trying to understand how the capability is exercised in the end, and bumped into this issue. Reading the website or the spec it was not immediately clear to me that the client has to issue a separate UCAN to the resource owner to actually exercise the capability.
It seems like there has to be something that would authenticate the caller with the service, is that correct?
Say, a Server issues an admin token to Alice, then Alice gives an attenuated token to Bob. Then when Bob calls the Server, Bob creates a new UCAN as far as I understand, but the Server still needs a way to verify that Bob is actually Bob, right? Or am I missing something?


Allow slayer norms to use parameters

User story
As a user, I want to modify the arguments to slayer neuron norms.
The neuron norms provide arguments to adjust momentum and other parameters:
https://github.com/lava-nc/lava-dl/blob/543efaac136bfb028f1445f0384fe36555c0fc21/src/lava/lib/dl/slayer/neuron/norm.py#L36
However, when used the neuron calls the constructor with no arguments:
https://github.com/lava-nc/lava-dl/blob/543efaac136bfb028f1445f0384fe36555c0fc21/src/lava/lib/dl/slayer/neuron/base.py#L146
As a workaround it might be possible to use a lambda function as the norm argument:
params = {
    "norm": lambda x: slayer.neuron.norm.MeanOnlyBatchNorm(momentum=0.2)
}

Thank you for this suggestion. @bamsumit Could you take a look, when you find some time :)

@Gavinator98 The intended usage pattern is to call a lambda like you mention. This is by design because the norm could have other signatures and therefore cannot be known in advance.


Check specs that are linked to from the body of a spec but not referenced

Sometimes, specifications link to a particular specification within the body of the spec but do not list that specification in the list of references. It would be useful to report such problems.

done in #47


Add Cursor Effects

Add Animated Cursor effects for Site's homepage -
Take Reference from -
https://blog.hubspot.com/website/animated-cursor
https://codemyui.com/tag/mouse-pointer/
Rules -

Comment below to Get Assigned
The PR Should be sent within 48 hours of Assignment, else will get reassigned to the next person.
The PR should be valid and have no Merge Conflicts
DON'T spoil the Code indentations with any formatting tools such as prettier or VSC format

Hello, do you have any preferred cursor effect in mind or any one works?

hi can you please assign it to me

@gaurav-iitb Assigned

@mo-renike Any decent, creative and Smooth Cursor Effect works for this.

@gaurav-iitb updates?


Add experimental Python Functions CNB to heroku/builder:22

Adds experimental support for Python Salesforce Functions to heroku/builder:22, to support the Python Functions alpha/beta release.
For now, this buildpack only passes detection for Python functions (projects that contain Python related files, such as requirements.txt, and also contain a project.toml with a com.salesforce.type of "function"). The buildpack is also only uploaded to S3 for now - later it will be published to Docker Hub and the upstream CNB registry.
For any other Python projects this buildpack will not pass detection, so this builder image will act as it did before (i.e.: not yet support them).
This PR adds the sf generate function template Python function under the examples directory, which is then built and tested with a health check request (like the other functions examples) in CI.
See also:
https://github.com/heroku/buildpacks-python/compare/functions-experimental
https://github.com/heroku/buildpacks-python/actions/runs/3661415824
https://github.com/heroku/sf-functions-python
GUS-W-12171308.

Post merge, I was able to successfully deploy a Python function to an org:
$ sf deploy functions --connected-org <SNIP>
remote: Compressing source files... done.
remote: Building source:
remote: [pythonfunction] heroku/python-functions-experimental 0.1.0
remote: [pythonfunction] Previous image with name "*****/<SNIP>/pythonfunction" not found
remote: [pythonfunction] Layer cache not found
remote: [pythonfunction] Layer cache not found
remote: [pythonfunction]
remote: [pythonfunction] [Determining Python version]
remote: [pythonfunction] No Python version specified, using the current default of 3.11.1.
remote: [pythonfunction] To use a different version, see: https://devcenter.heroku.com/articles/python-runtimes
remote: [pythonfunction]
remote: [pythonfunction] [Installing Python]
remote: [pythonfunction] Downloading Python 3.11.1
remote: [pythonfunction] Python installation successful
remote: [pythonfunction]
remote: [pythonfunction] [Installing Pip]
remote: [pythonfunction] Installing pip 22.3.1, setuptools 65.6.3 and wheel 0.38.3
remote: [pythonfunction] Installation completed
remote: [pythonfunction]
remote: [pythonfunction] [Installing dependencies using Pip]
remote: [pythonfunction] Pip cache created
remote: [pythonfunction] Running pip install
...
remote: [pythonfunction] Successfully installed aiohttp-3.8.3 aiosignal-1.3.1 anyio-3.6.2 async-timeout-4.0.2 attrs-22.1.0 charset-normalizer-2.1.1 click-8.1.3 frozenlist-1.3.3 h11-0.14.0 httptools-0.5.0 idna-3.4 multidict-6.0.3 orjson-3.8.3 salesforce-functions-0.0.0 sniffio-1.3.0 starlette-0.23.1 structlog-22.3.0 uvicorn-0.20.0 uvloop-0.17.0 yarl-1.8.2
remote: [pythonfunction] Pip install completed
remote: [pythonfunction]
remote: [pythonfunction] [Validating Salesforce Function]
remote: [pythonfunction] Function passed validation.
remote: [pythonfunction] Adding layer 'heroku/python-functions-experimental:dependencies'
remote: [pythonfunction] Adding layer 'heroku/python-functions-experimental:python'
remote: [pythonfunction] Adding 1/1 app layer(s)
remote: [pythonfunction] Adding layer 'launcher'
remote: [pythonfunction] Adding layer 'config'
remote: [pythonfunction] Adding layer 'process-types'
remote: [pythonfunction] Adding label 'io.buildpacks.lifecycle.metadata'
remote: [pythonfunction] Adding label 'io.buildpacks.build.metadata'
remote: [pythonfunction] Adding label 'io.buildpacks.project.metadata'
remote: [pythonfunction] Setting default process type 'web'
remote: [pythonfunction] Saving *****/<SNIP>/pythonfunction...
remote: [pythonfunction] *** Images (sha256:ed4dd37a52367752ef2b26e157afef8ae00cb6e1dbd2a655feca16d8993b7624):
remote: [pythonfunction]       *****/<SNIP>/pythonfunction:<SNIP>
remote: [pythonfunction] Layer cache not found
remote: [pythonfunction] Adding cache layer 'heroku/python-functions-experimental:pip-cache'
remote: [pythonfunction] Adding cache layer 'heroku/python-functions-experimental:python'
remote: Verifying deploy... done.
To https://git.heroku.com/<SNIP>.git
 * [new branch]      main -> master
Reference for testproject-pythonfunction created
Pushing changes to functions... done


Napari crash after registration

Hi,
I really like your plugin !, very well done and easy to use.
I have an issue when the registration is done, Napari crashes and close, BUT the files are created as expected.
I would like to see the result in Napari instead of if crashing if possible .
here is a copy of the log :
Creating the TransformParameterFile took 0.04s
Registration result checksum:<PHONE_NUMBER>
Final metric value  = -0.717203
Settings of AdaptiveStochasticGradientDescent for all resolutions:
( SP_a<PHONE_NUMBER>98<PHONE_NUMBER>08<PHONE_NUMBER>63<PHONE_NUMBER>43 69180.222893 13244.827490 4095.628960 1984.522654 501.394536 50.784041 )
( SP_A 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 )
( SP_alpha 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 )
( SigmoidMax 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 )
( SigmoidMin -0.018188 -0.032507 -0.027833 -0.048982 -0.175360 -0.765764 -0.855837 -0.932123 -0.953645 -0.953852 )
( SigmoidScale 0.000000 0.000000 0.000000 0.000000 0.000000 0.000001 0.000002 0.000003 0.000008 0.000033 )
Time spent on saving the results, applying the final transform etc.: 60 ms.
using default compression
saving to Y:\REGISTRATION DAPI\registration skin brain 5um dapi\register\brain\test2\testsimilaritaffine-b1_to_b2_registered.ome.tiff
transforming : 0
transformed : 0
saving
writing channel 0 - shape: (19365, 20145)
pyramid index 1 : channel 0 shape: (9682, 10072)
pyramid index 2 : channel 0 shape: (4841, 5036)
pyramid index 3 : channel 0 shape: (2420, 2518)
pyramid index 4 : channel 0 shape: (1210, 1259)
pyramid index 5 : channel 0 shape: (605, 629)
using default compression
saving to Y:\REGISTRATION DAPI\registration skin brain 5um dapi\register\brain\test2\testsimilaritaffine-b3_to_b2_registered.ome.tiff
transforming : 0
transformed : 0
saving
writing channel 0 - shape: (19365, 20145)
pyramid index 1 : channel 0 shape: (9682, 10072)
pyramid index 2 : channel 0 shape: (4841, 5036)
pyramid index 3 : channel 0 shape: (2420, 2518)
pyramid index 4 : channel 0 shape: (1210, 1259)
pyramid index 5 : channel 0 shape: (605, 629)
C:\python39\site-packages\ome_types_convenience.py:106: FutureWarning: The default XML parser will be changing from 'xmlschema' to 'lxml' in version 0.4.0.  To silence this warning, please provide the parser argument, specifying either 'lxml' (to opt into the new behavior), or'xmlschema' (to retain the old behavior).!
C:\Python39\site-packages\ome_types_convenience.py:106: FutureWarning: The default XML parser will be changing from 'xmlschema' to 'lxml' in version 0.4.0.  To silence this warning, please provide the parser argument, specifying either 'lxml' (to opt into the new behavior), or'xmlschema' (to retain the old behavior).!
and crash !
Not sure where the issue is coming from but if you have an idea that will be great !
thanks,

That's strange, what you are showing indicates the data was registered and the images written, so it must be on the reload... Can you double check the output folder and verify new OME-TIFFs are generated?

thank for the response , yes the files are generated, I can open them in FIJI without any problem.
Not sure where the problem comes from, memory issue perhaps ?
Also, with your plugin is there any way to affine manually the registration ?, it works well but not accurate I have a large shift in the final registration which need to be corrected manually somehow.
Or any suggestion to perform the registration ?
I can share my images as well , perhaps that will make it easier to visualize the issue ?
Thanks

Hi @Nal44 There are some ways to use wsireg to prepare images so you shouldnt need an initial affine transform. If you share your images, and relevant info like spatial resolution of the images, I can make a quick demo to explain. It may be easier than me trying to type it all out here.

Sure thanks a lot :) ,
I really appreciate your help,
I can share the file via my institution dropbox, can you send me your email ?
Rational of the project :
The images are consecutives sections tile scans , all taken at 20x using DAPI.
The idea is to register image 1 to image 2, and image 3 to image 2, and combine all 3.
I want to know the overlap of the sections (5um section) and estimate the % of overlap.
Depending on the results I want to perform serial sections staining then register to have data per nucleus ( hence I need accurate alignment).
Hence the registration is a crucial step to measure if the strategy is worth pursuing or find something else.
thanks a lot,

You can send a Dropbox link to @.***
On Sat, Apr 22, 2023, 12:03 PM Nal44 @.***> wrote:

Sure thanks a lot :) ,
I really appreciate your help,
I can share the file via my institution dropbox, can you send me your
email ?
Rational of the project :
The images are consecutives sections tile scans , all taken at 20x using
DAPI.
The idea is to register image 1 to image 2, and image 3 to image 2, and
combine all 3.
I want to know the overlap of the sections (5um section) and estimate the
% of overlap.
Depending on the results I want to perform serial sections staining then
register to have data per nucleus ( hence I need accurate alignment).
Hence the registration is a crucial step to measure if the strategy is
worth pursuing or find something else.
thanks a lot,
—
Reply to this email directly, view it on GitHub
https://github.com/NHPatterson/napari-wsireg/issues/8#issuecomment-1518706201,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AEIHKFGM6BGRVE7FDQCTKS3XCQFODANCNFSM6AAAAAAW2TOIHY
.
You are receiving this because you commented.Message ID:
@.***>

I sent you a share file invite on your vanderbilt email address.
Please dont hesitate to ask if you have any questions,
Really appreciate your help ,
Thanks a lot,

Hello again, I did not receive any invitation.

Hello, ok , just resend on your vanderbilt and gmail addresses.
Let me know if it works, please.
Thanks

Worked this time, thanks.
Heath
On Mon, Apr 24, 2023 at 1:12 PM Nal44 @.***> wrote:

Hello, ok , just resend on your vanderbilt and gmail addresses.
Let me know if it works, please.
Thanks
—
Reply to this email directly, view it on GitHub
https://github.com/NHPatterson/napari-wsireg/issues/8#issuecomment-1520617014,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AEIHKFDLP4ZRRKNGR4B43GTXC267NANCNFSM6AAAAAAW2TOIHY
.
You are receiving this because you commented.Message ID:
@.***>

Hi ,
any luck with my images ?
thanks

hi,
Any updates ?
mainly I want to know the type of registration i need to apply (rigid, similarity ,affine, combo ?) .
That would be really helpful.
thanks

Hi @Nal44  I did download your data and it worked ok for me. I will get back to you later this week, early next week. Apologies for the delay.
I think for your case, a rigid -> nl would be good or rigid -> affine -> nl
nl is non-linear, or non-rigid type registration.

Hi,
Ok thanks a lot, no problem for the delay, we are all super busy...
thanks for taking the time,
One more question :
how to deal with TIFF with multiple channels ? like Dapi + staining x +staining y  ... ?
Does it work the same ?
We could also do zoom call if this is easier to discuss,
thanks,
antho


Update google-cloud-nio to 0.123.8

Updates com.google.cloud:google-cloud-nio from 0.123.3 to 0.123.8.
GitHub Release Notes - Changelog - Version Diff
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "com.google.cloud", artifactId = "google-cloud-nio" } ]

labels: library-update, semver-patch

Superseded by #717.


Error: No Paths Provided -- .markdown-confluence.json folderToPublish not being used properly?

Issue Description
I am trying to publish an Azure DevOps Wiki from Markdown that was exported into Confluence. Aside from the requirement of files and folders to be uniquely named, I tried with a fresh folder and file structure. I still received the Error: No Paths Provided error (because it was red).
However, when I leave folderToPublish as just . or current directory, it works just fine. I then have to control where I'm getting my markdown files from by setting the contentRoot key.
❓ Why does anything other than "folderToPublish": "." seem to cause this issue?
I also have other issues like index.md not seemingly being published? That's a different ticket.
Evidence
The Error
➜  grc-docs-wiki git:(main) ✗
./markdown-container.sh
┌──────────────────────────────┐
│                              │
│   Error: No Paths Provided   │
│                              │
└──────────────────────────────┘

Bash script to run container
#!/usr/bin/env bash
#

export ATLASSIAN_API_TOKEN=$(cat .apitoken)
podman run \
  --interactive \
  --tty \
  --rm \
  --mount="type=bind,source=$(pwd),destination=/content,relabel=shared" \
  --userns=keep-id \
  --env="ATLASSIAN_API_TOKEN" \
  ghcr.io/markdown-confluence/publish:latest \
    "${@}"

.markdown-confluence.json
{
    "confluenceBaseUrl": "https://symplr.atlassian.net",
    "confluenceParentId": "274570412556",
    "atlassianUserName"<EMAIL_ADDRESS>    "contentRoot": "./phil/",
    "folderToPublish": "thingy",
    "firstHeadingPageTitle": true
}

The folder structure
➜  grc-docs-wiki git:(main) ✗
tree phil
phil
├── index.md
└── thingy
    ├── dude
    │   └── stuff
    └── mydude.md

4 directories, 2 files

I experienced the same issue.  It was quite confusing.  This issue at least let me know how to get it working to test.


Fixed #25579 - Reintroduced get_prep_value() method for ArrayField class

Related ticket.

I think it would be better if we could finish https://github.com/django/django/pull/6131 first so we can reuse the test classes there.

I've merged the other fix in 2495023a4cae28f494d0a6172abfac3a47a0b816. Could you try to rebase your branch and use classes introduced there? I left a comment on the ticket about an example query that could serve as a regression test. Thanks! p.s. You can squash commits and follow the commit message guidelines as described on the patch review checklist.

Yep, I shall do all that shortly.
I appreciate your guidance and patience, as I'm sure other Django dev newbies do too.

buildbot, add to whitelist.

merged in e7e5d9b338cabaafc61b7a0c55ff395b533d8c9e, thanks!


Fix custom setter dictionary crash when multithreading(#436)

Fix crash by moving custom setter name generation to __inspectProperties__ method.
@billinghamj Do you have unit test cases I can run with? to check the fix won't break other parts.

Excellent, thank you.
I don't have unit tests, but I believe there are some in #436 which you can use.

Oh but yes, sorry, there are unit tests you can run to check it still works. Use the Examples directory. Just run pod install in there, then you can run the tests inside Xcode

Also ignore the failed build - Travis CI doesn't work yet.

OK. I just run the tests against my branch. All tests passed.
I also added a new test case for concurrency.

hi ,
how to use CoocaPods update your commit

@ceekay1991 You can use pod 'JSONModel', :git => 'https://github.com/robinzhangx/jsonmodel.git', :branch => 'crash-fix'

@robinzhangx Could you rebase this onto master? Then Jenkins should run correctly

Travis* not Jenkins:)

Have also made a few minor notes, but otherwise looks excellent

We should probably move the custom getter resolution into this initialisation step too.

@billinghamj I also moved customGetter resolution to __inspectProperties.

@robinzhangx Thanks :) Really appreciate you taking the time to do this 👍

May I ask why it works? It seems that in this pr the parse procedure is moved from __customSetValue:forProperty: into __inspectProperties. But why in this way we can avoid the multithread problem?

Previously, setters/getters were resolved and cached on-demand. Now, they are all resolved during the initial JSONModel class inspection (which only happens once).
The caching part was what caused problems earlier. While the access to the cache object could have been synchronised, this would have slowed down the setting process.

Oh, I missing the fact that access of the value for keykClassPropertiesKey is atomic.
Thanks for the explanation!