Vulnerability roundup 111: tensorflow-2.4.4: 53 advisories [9.8]

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[ ] CVE-2022-23587 CVSSv3=9.8 (nixos-21.11)
[ ] CVE-2022-21726 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-21727 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-21740 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23558 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23559 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23560 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23561 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23562 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23566 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23573 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-23574 CVSSv3=8.8 (nixos-21.11)
[ ] CVE-2022-21728 CVSSv3=8.1 (nixos-21.11)
[ ] CVE-2022-21730 CVSSv3=8.1 (nixos-21.11)
[ ] CVE-2022-23590 CVSSv3=7.5 (nixos-21.11)
[ ] CVE-2022-23591 CVSSv3=7.5 (nixos-21.11)
[ ] CVE-2022-21725 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21729 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21731 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21732 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21733 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21734 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21735 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21736 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21737 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21738 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21739 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-21741 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23557 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23564 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23565 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23567 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23568 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23569 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23570 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23571 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23572 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23575 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23576 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23577 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23579 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23580 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23581 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23582 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23583 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23584 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23585 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23586 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23588 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23589 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23595 CVSSv3=6.5 (nixos-21.11)
[ ] CVE-2022-23563 CVSSv3=6.3 (nixos-21.11)
[ ] CVE-2022-23578 CVSSv3=4.3 (nixos-21.11)

CVE details
CVE-2022-23587
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21726
Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21727
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes axis + 1, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21740
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseCountSparseOutput is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23558
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in TfLiteIntArrayCreate. The TfLiteIntArrayGetSizeInBytes returns an int instead of a size_t. An attacker can control model inputs such that computed_sizeoverflows the size ofint` datatype. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23559
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both embedding_size and lookup_size are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.
CVE-2022-23560
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. Users are advised to upgrade as soon as possible.
CVE-2022-23561
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23562
Tensorflow is an Open Source Machine Learning Framework. The implementation of Range suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23566
Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in Grappler. The set_output function writes to an array at the specified index.  The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23573
Tensorflow is an Open Source Machine Learning Framework. The implementation of AssignOp can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23574
Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's SpecializeType which results in heap OOB read/write. Due to a typo, arg is initialized to the ith mutable argument in a loop where the loop index is j. Hence it is possible to assign to arg from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-21728
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ReverseSequence does not fully validate the value of batch_dim and can result in a heap OOB read. There is a check to make sure the value of batch_dim does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of Dim would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21730
Tensorflow is an Open Source Machine Learning Framework. The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23590
Tensorflow is an Open Source Machine Learning Framework. A GraphDef from a TensorFlow SavedModel can be maliciously altered to cause a TensorFlow process to crash due to encountering a StatusOr value that is an error and forcibly extracting the value from it. We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected.
CVE-2022-23591
Tensorflow is an Open Source Machine Learning Framework. The GraphDef format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a GraphDef containing a fragment such as the following can be consumed when loading a SavedModel. This would result in a stack overflow during execution as resolving each NodeDef means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21725
Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21729
Tensorflow is an Open Source Machine Learning Framework. The implementation of UnravelIndex is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21731
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ConcatV2 can be used to trigger a denial of service attack via a segfault caused by a type confusion. The axis argument is translated into concat_dim in the ConcatShapeHelper helper function. Then, a value for min_rank is computed based on concat_dim. This is then used to validate that the values tensor has at least the required rank. However, WithRankAtLeast receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that min_rank is a 32-bits value and the value of axis, the rank argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21732
Tensorflow is an Open Source Machine Learning Framework. The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory. This is because the num_threads argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21733
Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21734
Tensorflow is an Open Source Machine Learning Framework. The implementation of MapStage is vulnerable a CHECK-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21735
Tensorflow is an Open Source Machine Learning Framework. The implementation of FractionalMaxPool can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21736
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value. The 3 input arguments to SparseTensorSliceDataset represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21737
Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21738
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseCountSparseOutput can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21739
Tensorflow is an Open Source Machine Learning Framework. The implementation of QuantizedMaxPool has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21741
Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23557
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in BiasAndClamp implementation. There is no check that the bias_size is non zero. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23564
Tensorflow is an Open Source Machine Learning Framework. When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23565
Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a SavedModel on disk such that AttrDefs of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23567
Tensorflow is an Open Source Machine Learning Framework. The implementations of Sparse*Cwise* ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or CHECK-fails when building new TensorShape objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23568
Tensorflow is an Open Source Machine Learning Framework. The implementation of AddManySparseToTensorsMap is vulnerable to an integer overflow which results in a CHECK-fail when building new TensorShape objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23569
Tensorflow is an Open Source Machine Learning Framework. Multiple operations in TensorFlow can be used to trigger a denial of service via CHECK-fails (i.e., assertion failures). This is similar to TFSA-2021-198 and has similar fixes. We have patched the reported issues in multiple GitHub commits. It is possible that other similar instances exist in TensorFlow, we will issue fixes as these are discovered. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23570
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a DCHECK. However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-23571
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments, if the tensors have an invalid dtype and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23572
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the DCHECK function however, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the ValueOrDie line. This results in an assertion failure as ret contains an error Status, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-23575
Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23576
Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateOutputSize is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements.  The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23577
Tensorflow is an Open Source Machine Learning Framework. The implementation of GetInitOp is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23579
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that SafeToRemoveIdentity would trigger CHECK failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23580
Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23581
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that IsSimplifiableReshape would trigger CHECK failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23582
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures. TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23583
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that any binary op would trigger CHECK failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the dtype no longer matches the dtype expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If Tin and Tout don't match the type of data in out and input_* tensors then flat<*> would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a CHECK crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23584
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a use after free behavior when decoding PNG images. After png::CommonFreeDecode(&decode) gets called, the values of decode.width and decode.height are in an unspecified state. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23585
Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling png::CommonInitDecode(..., &decode), the decode value contains allocated buffers which can only be freed by calling png::CommonFreeDecode(&decode). However, several error case in the function implementation invoke the OP_REQUIRES macro which immediately terminates the execution of the function, without allowing for the memory free to occur. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23586
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that assertions in function.cc would be falsified and crash the Python interpreter. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23588
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that Grappler optimizer would attempt to build a tensor using a reference dtype. This would result in a crash due to a CHECK-fail in the Tensor constructor as reference types are not allowed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23589
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23595
Tensorflow is an Open Source Machine Learning Framework. When building an XLA compilation cache, if default settings are used, TensorFlow triggers a null pointer dereference. In the default scenario, all devices are allowed, so flr->config_proto is nullptr. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23563
Tensorflow is an Open Source Machine Learning Framework. In multiple places, TensorFlow uses tempfile.mktemp to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in mktemp and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the mktemp function usage. We have patched the issue in several commits, replacing mktemp with the safer mkstemp/mkdtemp functions, according to the usage pattern. Users are advised to upgrade as soon as possible.
CVE-2022-23578
Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of ImmutableExecutorState::Initialize. Here, we set item->kernel to nullptr but it is a simple OpKernel* pointer so the memory that was previously allocated to it would leak. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Scanned versions: nixos-21.11: 2128d0aa28e.
Cc @abbradar
Cc @jyp

21.11 is EOL


For an artifact, n_objects should never be None

If we want to achieve this, we might need to drop direct upload from .zarr, @Koncopd.

Not planned. .n_objects is None for file-like artifacts. For folder-like artifacts, it's an integer.


News Ticker Dialog box wont't close after hitting add/edit/delete for news items

I click edit web part.
I click Manage News Items
After I choose to add, edit, or delete an item, when I click ok the dialog box remains open and I cannot exit out of the "Mangage News Items" page. I have to reload the entire page. (The items are still added/edited/deleted on refresh but I shouldn't have to do that).
If I don't select add, edit, or delete and instead want to just close the Manage News Items dialog box, It does close the options to add/edit/delete the items and I no longer see them as available. However, the external Manage News items dialog box remains without any option to close it (and I still have to manually refresh the page) .

This happened in news carousal webpart as well. Is there any solution or quick fix that you have?


setinterception doesn't capture all outgoing requests generated by the page

Steps to reproduce
I am using jest-puppeteer and jest-preset.
Tell us about your environment:

Puppeteer version: 1.8.0
Platform / OS version: mac OS high sierra
URLs (if applicable): www.nike.com
Node.js version: v8.11.0

What steps will reproduce the problem?

Visit Nike's website using: page.goto('https://nike.com', {waitUntil: 'networkidle2'});
Look for network requests generated by the page using:
await page.setRequestInterception(true);
let url = [];
page.on('request', interceptedRequest => {
url.push(interceptedRequest.url());
console.log('requests checkpoint 1', url);
interceptedRequest.continue();
});

Please include code that reproduces the issue.

page.goto('https://nike.com', {waitUntil: 'networkidle2'});

await page.setRequestInterception(true);
let url = [];
page.on('request', interceptedRequest => {
url.push(interceptedRequest.url());
console.log('requests checkpoint 1', url);
interceptedRequest.continue();
});

What is the expected result?
I am hoping to get a list of all the request urls made by nike.com page.
What happens instead?
Sometimes I get empty list (0 request urls), other times I get 2-3 request urls instead of 30 urls.

The following gives me 100+ requests reliably. Maybe you don't await the page.goto command?
const pptr = require('puppeteer');

(async() => {
  const browser = await pptr.launch();
  const page = await browser.newPage();
  const urls = [];
  await page.setRequestInterception(true);
  page.on('request', request => {
    urls.push(request.url());
    request.continue();
  });
  await page.goto('https://nike.com', {waitUntil: 'networkidle2'});
  console.log(urls.length);
  await browser.close();
})();

@aslushnikov thanks. It works. :) :)


Bookmark link broken

The bookmark link in the README doesn't work. Apparently GitHub's markdown doesn't support javascript links (https://github.com/github/markup/issues/79), it might be an idea to use GitHub Pages?

That is, actually, a GitHub page! Just go to
https://retrography.github.io/VUTt
On September 4, 2017 at 12:02:30 PM, Casper Boone<EMAIL_ADDRESS>wrote:

The bookmark link in the README doesn't work. Apparently GitHub's markdown
doesn't support javascript links (github/markup#79
https://github.com/github/markup/issues/79), it might be an idea to use
GitHub Pages?
—
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Reply to this email directly, view it on GitHub
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.

Ah, cool! Missed that ;)


⚠ Melody Beta has degraded performance

In 3d16e4e, Melody Beta (https://canary.melody.api.triza.dev) experienced degraded performance:

HTTP code: 200
Response time: 3506 ms

Resolved: Melody Beta performance has improved in 1b83cd6.


Back to top added

Description
Back to top added
Fixes #31
Type of change

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

How Has This Been Tested?
https://user-images.githubusercontent.com/55352601/115504123-0d2fdf00-a295-11eb-8ad7-e6fb1a66d229.mp4
Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have been merged and published in downstream modules

@vikasdo @Akshay6890 kindly review my PR

Sure
On Wed, 21 Apr 2021, 11:35 111arpit1, @.***> wrote:

@vikasdo https://github.com/vikasdo @Akshay6890
https://github.com/Akshay6890 kindly review my PR
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@vikasdo could you please add labels to it


Feature/wip redfish

First pass on adding Redfish 1.0:

Service Root and Systems GET implemented
Responses are templatized
Responses are validated against the official json-schema
Swagger UI is registered

@RackHD/corecommitters @tannoa2 @keedya @uppalk1

+1
Follow up addition depedent of this PR: https://github.com/jlongever/on-http/commit/2ca036185f00e168841b7569fa2a52f63275f2ea

:+1:


Add persistent storage for DefaultOTAProviders attribute

Problem
Added support for loading and storing the default OTA provider attribute
Change overview

A generic storage interface for the OTA provider
A generic implementation for the OTAStorageProvider
Load/Store the defaultotaproviderList attribute in the KVS
Removed the "Optional" nature of the ProviderLocationList class (mList var) to make it easier to copy buffers from/to the KVS, without having an intermediate buffer.

Testing

Tested using chip-tool and REPL.
Wrote defaultotaproviderList and ensured it was stored to the KVS and read-back from it
Ensured the defaultotaproviderList value was read from KVS during bootup

@hrajendran-samsung I started crafting the storage interface for provider location and update token in https://github.com/project-chip/connectedhomeip/pull/15483. I will mark it as draft not to create conflicts with your changes, but let me know if it can be useful for you :)

@hrajendran-samsung I started crafting the storage interface for provider location and update token in #15483. I will mark it as draft not to create conflicts with your changes, but let me know if it can be useful for you :)

Thanks @Damian-Nordic :-) . I believe your PR addresses Tennessee's comments in general. I will close this PR- we should simply merge yours instead.

@hrajendran-samsung Ok to close this now that it is being addressed in https://github.com/project-chip/connectedhomeip/pull/15483?


Non-unique SID in policy

Description
When using repository_read_write_access_arns, a duplicate SID is created in the IAM policy document.  Multiple dynamic statements keyed to repository_read_write_access_arns use the same ReadWrite SID.
https://github.com/terraform-aws-modules/terraform-aws-ecr/blob/124c13976f4cdc061f5b1ddb38bff715eeba2ad5/modules/repository-template/main.tf#L104
https://github.com/terraform-aws-modules/terraform-aws-ecr/blob/124c13976f4cdc061f5b1ddb38bff715eeba2ad5/modules/repository-template/main.tf#L124

[ ] ✋ I have searched the open/closed issues and my issue is not listed.

Versions

Module version [Required]: 2.3.0, master

Terraform version: Any, doesn't matter

Reproduction Code [Required]

Steps to reproduce the behavior:
Set any value for the repository_read_write_access_arns variable
Expected behavior
Work mo betta.  Basically have different SID values for the two lines linked at the top of this report
Actual behavior
Error: writing IAM Policy Document: duplicate Sid (ReadWrite). Remove the Sid or ensure the Sid is unique

we are unable to help troubleshoot without a reproduction
we do set these values in the examples and they work without issue

https://github.com/terraform-aws-modules/terraform-aws-ecr/blob/124c13976f4cdc061f5b1ddb38bff715eeba2ad5/examples/complete/main.tf#L35
https://github.com/terraform-aws-modules/terraform-aws-ecr/blob/124c13976f4cdc061f5b1ddb38bff715eeba2ad5/examples/complete/main.tf#L66

This is specifically for the repository-template submodule, see links above.  Your examples for the submodule don't use that variable, so they don't encounter the bug.  It's very obvious, it's two statements with the same sid, one of the two lines I linked needs to be changed to a different sid.  I'll submit a patch tomorrow.

This issue has been resolved in version 2.3.1 :tada:


Benchmarking

We need benchmarks for speed and memory usage for all the layers. Right now it's hard to predict run time of a new algorithm.

Commit<PHONE_NUMBER>c0a709fe322ab146a9786cf6f2f01e
added basic benchmarks for FullAtomModel.Angles2Coords, RMSD.Coords2RMSD and ReducedModel.Angles2Backbone. Also, added comparative time scales from LSTM


Upgrade: Finish Upgrade text stays after you click it, until you refresh

Rancher Version: v1.2.0-pre4-rc5
Steps to Reproduce:

Have a catalog template with at least 2 version
Add the template version 1
Click on upgrade available
Upgrade to version 2
Click on Upgrade: Finish Upgrade

Results: The upgrade finishes, but the button doesn't change it still says Upgrade: Finish Upgrade until you refresh the page (happens in stack detail and main stack page)

Expected:  Should switch to "Upgrade available" or "Up to date"

@tfiduccia I tried with the kubernetes template of infra-catalog, it had two versions

I clicked on upgrade available
then on upgrade
then without refresh it changed to Upgraded

@mrajashree - not using kubernetes environment.  Just plain cattle with standard catalog template.

@vincent99 I don't think it's a catalog-service bug since the calls corresponding to upgrade and finishUpgrade go to v2-beta/projects/1a5/stacks.

Version - master 11/06
Verified fixed


Rcoundown needs a color palette, to guide ui choices

Current ui colors feels one way, monotonic in a sense. It lacks "charm" which I believe can easily be gotten when a palette is defined for the project.
Palette proposals are all welcome.

🙃
On Sat, 19 Mar 2022, 21:48 Nathaniel, @.***> wrote:

Current ui colors feels one way, monotonic in a sense. It lacks "charm"
which I believe can easily be gotten when a palette is defined for the
project.
Palette proposals are all welcome.
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Tag a release

If this project is ready for beta or production use, please tag a commit with an appropriate number so we can use composer without dev-master.
Thanks!

Done, thanks for the reminder!


Solution explorer should not show "obj" folder

it should only show stuff that is part of the source

Won't fix, work on my machine, I don't like users


Fizzbuzz

This makes following python code runable:
def fizzbuzz(n):
    if n % 3 == 0 and n % 5 == 0:
        return "FizzBuzz"
    elif n % 3 == 0:
        return "Fizz"
    elif n % 5 == 0:
        return "Buzz"
    else:
        return str(n)

n = 1
while n < 10:
    print(fizzbuzz(n))
    n += 1

Right, thanks.

I realised those were fairly minor nitpicks, so I've pushed the changes up myself.


Fatal error on RSS-Bridge 2018-09-09

Fatal error on RSS-Bridge 2018-09-09 using FB2 Bridge.

PHP Fatal error:  Cannot redeclare extractFromDelimiters() (previously declared in C:\rss-bridge\lib\html.php:78) in C:\rss-bridge\bridges\FB2Bridge.php on line 20
Fatal error: Cannot redeclare extractFromDelimiters() (previously declared in C:\rss-bridge\lib\html.php:78) in C:\rss-bridge\bridges\FB2Bridge.php on line 20

Should be fixed now

My bad, missed this occurence of the function. Thank you @teromene for the quick fix.


New '--make-summary-multiline' option

This is not recommended by the PEP 257, but there are some project that
use it in this way. So, a new '--make-summary-multiline' option is added
to allow those project to be able to use the rest of the docformatter
features.
When this option is set as True and use docformatter over a function
like this one:
def function():
    """This is a one line summary that will be converted to multiline."""

the result will be:
def function():
    """
    This is a one line summary that will be converted to multiline.
    """

Coverage decreased (-0.4%) to 99.65% when pulling c88af2de7149e6f057b067c830d2cb1a60c51af5 on humitos:master into 252aead22d1855391718931e7760da20b823b9a0 on myint:master.

Coverage decreased (-0.4%) to 99.65% when pulling c88af2de7149e6f057b067c830d2cb1a60c51af5 on humitos:master into 252aead22d1855391718931e7760da20b823b9a0 on myint:master.

Coverage decreased (-0.4%) to 99.65% when pulling c88af2de7149e6f057b067c830d2cb1a60c51af5 on humitos:master into 252aead22d1855391718931e7760da20b823b9a0 on myint:master.

Thanks.

@humitos, please see<PHONE_NUMBER>3f1911bb0d67ee26fdcfad709981b8. I've merged your option into the existing --pre-summary-newline. Let me know if this is adequate.

Well, as my change doesn't follow strictly the PEP257 I'm not sure if we should merge it into --pre-summary-newline since that both option (True or False) for this one are good by PEP257.
I mean, these two options are PEP257 compatible

without --pre-summary-newline

 def factorial(x):
-    """Return x factorial. This uses math.factorial."""
+    """Return x factorial.
+
+    This uses math.factorial.
+
+    """
     import math
     return math.factorial(x)

with --pre-summary-newline

 def factorial(x):
-    """Return x factorial. This uses math.factorial."""
+    """
+    Return x factorial.
+
+    This uses math.factorial.
+
+    """
     import math
     return math.factorial(x)

If we merge --make-summary-multiline into --pre-summary-newline we will be forcing the user to use both at the same time. I prefer more flexibility.
So, I think it's better to leave it as a new option so the final user can customize as he/she wants to get the right behavior. I wouldn't merge both options into the same one.

Good point. I've undone my merging of the two options. I did rename it slightly though to --make-summary-multi-line. I've been a bit inconsistent in the spelling throughout the repository, but I might as well make the spelling match PEP 257.
Thanks

Perfect, thanks!


HTML5 doctype is case insensitive

https://html.spec.whatwg.org/multipage/syntax.html#the-doctype
doctype-first reports that the doctype isn't found when it is not in caps, even with doctype-html5 set to true.

Thanks for the report and sorry about the delay. Pretty simple fix.


Update eslint-plugin-react and enable new rules

Some new rules had been added that are a good fit for this project. All of these are either already runtime warnings in React (no-danger-with-children, style-prop-object) or React features that are going to be deprecated in the future (no-find-dom-node). The new rules:

react/no-danger-with-children (yannickcr/eslint-plugin-react#710)
react/no-find-dom-node (yannickcr/eslint-plugin-react#678)
react/style-prop-object (yannickcr/eslint-plugin-react#715)

I also considered the new no-unused-prop-types rule, but wasn't sure if it would be a good fit here. Any thoughts on it @gaearon?

I think no-find-dom-node is a bit too early for this kit right now. It's okay for more mature setups but I'm worried beginners will copy and paste examples from StackOveflow and be confused by this warning.
I'm open to adding it in a year or so.

Alright, I removed no-find-dom-node. I think to be included in a beginner friendly configuration like CRA, the error message would also need to be better than the current Do not use findDOMNode, at least explain that you should use refs instead and possibly link to docs.

Exactly. (I'd appreciate if somebody did that.)

Is Travis acting up?

npm ERR! peerinvalid The package<EMAIL_ADDRESS>does not satisfy its siblings' peerDependencies requirements!
npm ERR! peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>
Uh, it installs<EMAIL_ADDRESS>from npm that still has the old<EMAIL_ADDRESS>as a peer dependency. I guess we shouldn't change the ESLint plugin versions in react-scripts until we publish  eslint-config-react-app with the new version? But then it fails when installing locally, because our local config depends on the new version... Tricky 😅

e2e script should use current versions of all packages, not ones from npm. Can we make it do that? Maybe need to run lerna bootstrap or whatever?

I’m going to trust that this works but we need to figure out the e2e fix for this.

https://github.com/facebookincubator/create-react-app/issues/698


Slow first calls to face_encodings()

face_recognition version:

>>> face_recognition.__version__
'1.2.3'

Python version:

$ python3 --version
Python 3.6.9

Operating System:

$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 18.04.4 LTS
Release:        18.04
Codename:       bionic

Note: On NVIDIA Jetson Nano
Description
Hi all, it seems that the very first call to face-locations/face-encodings methods are slower than future calls. In particular face_recognition.face_encodings() is taking a long time - looking through the code; it looks like it calls this:
pose_predictor_68_point = dlib.shape_predictor(predictor_68_point_model)

Is there a way to pre-warm this (if that's even feasible?)
It's the difference between:

First call:

Locations time: 2723
Encodings time: 1061

Future calls:

Locations time: 554
Encodings time: 38

What I Did
        locations_start = get_time_ms()
        face_locations = face_recognition.face_locations(
            rgb_small_frame,
            number_of_times_to_upsample=1,
            model="cnn")
        print(f"Locations time: {get_time_ms() - locations_start}")

        encodings_start = get_time_ms()
        face_encodings = face_recognition.face_encodings(
            rgb_small_frame, face_locations,
            num_jitters=1,
            model="large")
        print(f"Encodings time: {get_time_ms() - encodings_start}")

I am seeing akin behavior and I am able to reproduce it via the benchmark.py script provided by face_recgnition inside of the examples dir
when running this command I prefixed with time just to get an understanding of how long the script itself ran as individual tests seem to indicate the proper speed.

Timings at 240p:
 - Face locations: 0.0679s (14.73 fps)
 - Face landmarks: 0.0030s (335.78 fps)
 - Encode face (inc. landmarks): 0.0047s (213.45 fps)
 - End-to-end: 0.0671s (14.90 fps)

Timings at 480p:
 - Face locations: 0.2395s (4.18 fps)
 - Face landmarks: 0.0027s (371.71 fps)
 - Encode face (inc. landmarks): 0.0041s (245.03 fps)
 - End-to-end: 0.2451s (4.08 fps)

Timings at 720p:
 - Face locations: 0.5400s (1.85 fps)
 - Face landmarks: 0.0025s (397.96 fps)
 - Encode face (inc. landmarks): 0.0043s (231.60 fps)

 - End-to-end: 0.5481s (1.82 fps)

Timings at 1080p:
 - Face locations: 1.2067s (0.83 fps)
 - Face landmarks: 0.0025s (406.06 fps)
 - Encode face (inc. landmarks): 0.0043s (230.46 fps)
 - End-to-end: 1.2102s (0.83 fps)

real	30m8.689s
user	30m2.780s
sys	0m10.721s```

just some more evidence Nov 2021
Jetson Nano
dlib.DLIB_USE_CUDA = True
dlib version = 19.22.0
dlib compiled = Nov 14 2021 16:36:45
face_recognition.version = 1.2.3
cv2.version = 4.1.1
I also note that, not using the benchmark, the first call to face_recognition.face_locations with model="cnn"
will take 22seconds to return
subsequent calls take about 0.5 sec
if using model="hog" then the 1st call takes 0.6 sec as do all the subsequent calls.
Benchmarks (Note: All benchmarks are only using a single CPU core)
Timings at 240p:
 - Face locations: 0.2627s (3.81 fps)
 - Face landmarks: 0.0072s (139.34 fps)
 - Encode face (inc. landmarks): 0.0278s (35.97 fps)
 - End-to-end: 0.2887s (3.46 fps)

Timings at 480p:
 - Face locations: 1.0106s (0.99 fps)
 - Face landmarks: 0.0073s (136.88 fps)
 - Encode face (inc. landmarks): 0.0282s (35.48 fps)
 - End-to-end: 1.0451s (0.96 fps)

Timings at 720p:
 - Face locations: 2.2683s (0.44 fps)
 - Face landmarks: 0.0074s (135.88 fps)
 - Encode face (inc. landmarks): 0.0283s (35.37 fps)
 - End-to-end: 2.3093s (0.43 fps)

Timings at 1080p:
 - Face locations: 5.3314s (0.19 fps)
 - Face landmarks: 0.0075s (133.54 fps)
 - Encode face (inc. landmarks): 0.0286s (34.95 fps)
 - End-to-end: 5.3916s (0.19 fps)


Still says "saving"

When testing the portal I got to the profile creation page. After doing the Onfido step - I returned to the page clicked the blue button at the bottom and it has said Saving for the last 45 minutes... Not sure what's supposed to happen next.

This should be resolved. Can you check again?


Allow asymmetric length for shorthand beziers

Currently shorthand bezier handles are linked in both direction and length. Typically bezier handles, with symmetry enabled, allows for independent scaling of opposing handles.

Unlike other editors, GodSVG is just a middleman between the actual SVG code and you, so it can't behave like them here. Shorthand beziers in SVG are implemented by omitting an entire handle, so changing this isn't an option.
Something actionable here would be to add a keybind, like Shift, to force a bezier control handle to align with the previous one.

Closing as #531 documents this class of issues.


connector/github: fix username used when making API requests

Removed logic that used a GitHub users' display name over their login name. Login name will work in API requests while display name will not.
Fixes a bug where users with both a display name and login name would not see org membership correctly.
Tests: manual
Fixes #1032

Could you please elaborate on all the tests you performed manually and their output


Update fails on old records if recordSelector gets removed from module

Update of records fails with 502 when an recordSelector is removed from module.
To Reproduce
Create a Module with some fields and a record selector of another module.
Populate some records. Go back to the module and remove the recordsSelector field.
The formely created records of the module are still there but can not be edited anymore. (502) They can be deleted but not updated.
Expected behavior
Old records should still work if fields get added or removed from modules.
Screenshots
Hopefully not necessary ;)
Additional context
Version: 2021.3.2

Is this still an issue?


StringLiteralDuplication - 3/3 - [toString] unclear error

The following kotlin code gets flagged for me:
override fun toString() = """
    |
    |
    |
    |---
    |Android Version: $RELEASE ($SDK_INT)
    |App Version: ${versionCodeProvider.versionName} (${versionCodeProvider.versionCode})
    |Device: $MODEL ($MANUFACTURER/$BRAND)
    |Locale: ${Locale.getDefault()}
    """.trimMargin()

I'm unclear though what is causing the StringLiteralDuplication. Any hints?

Is there any code in the same file which looks like your toString multiline string :O ?

No. Only a data class with one parameter. My assumption is that $MODEL will call toString() under the hood and that might be reported?

I was able to reproduce it.
I think you have duplicated parts of the returned string from toString() in the same KtFile.
I give an example. Here "|Android Version: " has 3 usages. It seems like it treats the string before the $ operator as a separate string.
data class Data(val i: Int) {

	val str1 = "|Android Version: "
	val str2 = "|Android Version: "

	override fun toString() = """
|---
|Android Version: $RELEASE ($SDK_INT)""".trimMargin()

}

I have a fix ready in case the decision is made that this is not the desired behavior.

This is the entire file:
package com.vanniktech.common.android

import android.os.Build.BRAND
import android.os.Build.MANUFACTURER
import android.os.Build.MODEL
import android.os.Build.VERSION.RELEASE
import android.os.Build.VERSION.SDK_INT
import java.util.Locale

class ContactEmailBodyTemplate(
  private val versionCodeProvider: VersionCodeProvider
) {
  override fun toString() = """
      |
      |
      |
      |---
      |Android Version: $RELEASE ($SDK_INT)
      |App Version: ${versionCodeProvider.versionName} (${versionCodeProvider.versionCode})
      |Device: $MODEL ($MANUFACTURER/$BRAND)
      |Locale: ${Locale.getDefault()}
      """.trimMargin()
}

Still can't see what's triggering this.

Oh might it be the:
      |
      |
      |

If so we should exclude those.

@vanniktech
No, I don't think so. I think it would be easier to ignore such multiline strings.
I committed a fix locally which treats such a string as one object.

That would be much better yeah.


plugin not thread-safe, only synchronous input, does not track past events

I am currently working on a reimplementation of logstash-filter-throttle to suit the needs of my customer. The reason for this is that the current plugin:

is not thread-safe (*1)
only supports synchronous input: with multiple (redis) inputs things get async really quick
does not track past events: events before "Time.now - period" expire instantly

How it works: when an event is received, the key is stored in a key_cache. The key references a timeslot_cache. The event is allocated to a timeslot (created dynamically) based on the timestamp of the event. The counter is incremented. A second event (same key), within the same "period", is allocated to the same timeslot. The counter is incremented.
This way it is possible to process events from the past in an asynchronous manner. I would like to know whether Elastic would be interested in maintaining this new version of the plugin. Please let me know. I hope this thread is picked up soon and it does not remain unseen.
*1) addisonj already created a pull request for this, which is still not merged unfortunately: https://github.com/logstash-plugins/logstash-filter-throttle/pull/1

+1 Especially for the thread safety problem.

+1

I am wondering what is the status of this? We are using thread safe throttle.rb with Logstash 1.4.2 and it works great. But running it with 1.5.4 produces some errors and Logstash eventually stops working. This stops us from upgrading our environment to new version since we user throttle a lot with PagerDuty.

Reimplementation of logstash-filter-throttle plugin is pretty much done.
During development it has been put to the test with a test set of about 3 million events.
A new configuration item was added to specify the maximum age of a timeslot. Also, the memory control mechanism has been made adaptive (automatically adjusts timeslot max_age to prevent OOM).
We are currently using the plugin in our production environment.
I will fork the plugin, put code changes online, and create a pull request somewhere next week.
Still waiting for a sign of life from Elastic. Guess I need more +1...

Awesome! @frapex

I copied the file to 1.5.4 Logstash and tried it out. Well - it works fine until we hit throttle event. Once we do - Logstash stops sending ANY events. Not sure if this is our configs but they do work as expected in 1.4.2.

I am pretty sure it is your config, perhaps you can share it.
However, I am not sure whether this is the right thread to discuss your problem.

+1

+1

Solved, https://github.com/logstash-plugins/logstash-filter-throttle/pull/5 was merged


AWS Serverless Example

Creating this as a placeholder to add an example to https://github.com/awslabs/aws-serverless-java-container/issues/128
instead of a shaded jar, it would be interesting to use the layered jars to take advantage of SOCI for container pulls and Lambda’s SnapStart

if it's helpful, we used to attempt to deploy our dropwizard app in lambda using https://github.com/trib3/leakycauldron/blob/v1.27.2822/lambda/src/main/kotlin/com/trib3/lambda/TribeServerless.kt -- cold start times were too slow to be useful so we deprecated & then deleted the code, but it may be a useful starting point for anyone interested, as with snapstart the cold start problem may be solved.


laravel-generator config file not change

I change laravel-generator.php file but when I run
php artisan infyom:api Post
Create file with default value.
I change model address and namespace but not change

@yepco Can you post your laravel-generator.php and generated files here. I have tried to change model location and namespace and it worked fine.

Thanks
I solved it.
I have another question
I have json file and How I import it in php artisan command?

I Use this command
php artisan infyom:scaffold $MODEL_NAME$ --fieldsFile=absolute_file_path_or_path_from_base_directory


[MODEL] Update Mongoid example

I've updated the Mongoid example and successfully run it against elasticsearch versions 6.3.0 and 5.4.2 with Mongoid 7/MongoDB 3.6.

Closing in favor of this pull request.


Markdown-UI & Template-UI node do not process HTML\Markdown sent to it by NR Template node

When defining HTML or Markdown content in a nodered Template node and sending this to the new HTML and Markdown nodes, the content is not displayed as Markdown or HTML.

If I understand correctly I have the same issue. I am calling a remote function that returns HTML formatted text I want to display - using the HTML formatting. However I have not found a way to make this happen.
Here is my template (Widget, group scoped)

Here is what is displayed

The problem appears to be that my text is injected into the generated HTML as a quoted string - and because it is quoted the embedded html controls are ignored. This is what I see when I inspect my web page:

Thanks for your help
Colin

This is a very difficult thing to get right given the lifecycle of events that needs to take place. The steps are as follows:

Config for the node is received with content defined
Parse content and convert it from markdown to HTML
Bind the resulting HTML to the template of the Vue component

This triggers Vue internals to parse of any HTML tags, etc, and allow for injection of {{ msg.<stuff> }}

On receiving a new msg, we replace any appearances of {{ msg.<stuff> }} with the relevant value received
We run the renderMermaid function to parse any mermaid content

This falls over because it's possible for the {{ msg.<stuff> }} to contain HTML/Markdown, which is not re-parsed by VueJS at that point.

Commenting on the above I'm not sure it is clear what I'm saying:

when defining HTML content in a (non-ui) template node and sending it to the UI-template node (which should render HTML), this does not work

when defining Markdown in a (non-ui) template node and sending it to the UI-Markdown node (which should render Markdown) this does not work

And with "this does not work" I mean: the defined content is not displayed in the UI node, and we've even experienced lockups of the entire UI\Dashboard2 (by simply sending HTML to a UI-template node).
I am not asking to rewrite\convert markdown to HTML, that would not make sense (i.e. just use the correct content node). But I would like to be able to just define markdown as a template and send that to and have it rendered by the UI-Markdown node. Same for HTML.
Why: this allows to have one (1) markdown\html node on the dashboard the (entire) content of which can change dynamically.
And this was not working at the time of issue submission.

Hi Joe
Thanks for your quick reply.
I also experienced lockups of the entire dashboard when I was experimenting with this - Sorry, I did not pursue this to document exactly how to reproduce the issue. Now I have tidied my code that problem has gone away. If I hit it again I'll document the issue properly.
Re the text formatting. I was mislead by the HTML displayed by Chrome inspect. Copying to notepad I can see the problem is my text has had the HTML control characters escaped so that the exact text I supply is displayed. In most cases this is what is wanted...  But not always. To handle this we would need a switch - some way of telling the system not to escape the inserted text.
Markdown uses different controls, perhaps I can use this...
"To create paragraphs, use a blank line to separate one or more lines of text."
"To create a line break or new line (), end a line with two or more spaces, and then type return."
No joy :-(
The problem appears to be the Markdown processing is done before my text is inserted - the controls I put in the Markdown widget definition work as they should. The same controls in the inserted text do not.
Here is my markdown definition

Here is the generated HTML

Here is what I see on the dashboard

I think this is wrong. Text should be inserted before the markdown processing.
All I want to do is display a plain text log file. The only formatting I need is line feed. Is there another way?
Thanks again
Colin

This is similar to #715 "support HTML in msg.payload of ui-text."

@colin-grierson : discovered this week that using  {{msg.payload}}  in a ui-template node will display JSON in a (more or less) correct format. Maybe this is of some help..


v1.142-6eec8cf

RE7 (without TDB) dos't work . Why and what is it ?
...............
win10x64 21H2 | i5-4670K 4.5GHz | 16Гб DDR3 | MSI GTX1080ti GAMING X 11G | Oculus Quest2

got it - this is for the new version with RT
closed


Original sentence token position from coref_cluster

Hi,
doc._.coref_clusters returns a list of clusters. But how do I know which element of the cluster refers to which token in the original sentence? Is there a way to get the token position for each coreference?
For example, if one of the elements in coref_clusters is 'she', I would like to know which 'she' is the cluster referring to. Because there can be many 'she' in the original sentence.
Thanks in advance.

coref_clusters are coreferring mentions, and these NeuralCoref mentions are spaCy Span objects which means you can access all the usual Span attributes. For more information see https://github.com/huggingface/neuralcoref#using-neuralcoref.


Adding Multiple TLDS

I am working on a fork of ens-contracts and the goal is to support multiple TLDs like .eth, .btc, etc can this be done on the current version of contract and is there any guide to do so

We don't provide technical support for forks of our contracts.


CI for linux is temporarily broken

Description
CI is failing for linux because we switched the base image to use opensearch-build alma linux with gcc 12. It started showing up when static linking for blas was reenabled (#1665 )
This will be fixed when we revert to gcc docker image: https://github.com/opensearch-project/opensearch-build/pull/4663.
Error will look like:
/opensearch-knn/lib/libopensearchknn_faiss_avx2.so: ELF load command address/offset not properly aligned [in thread "opensearch[ip-10-0-3-160.us-west-2.compute.internal][write][T#6]"]

Waiting for: https://build.ci.opensearch.org/job/docker-build/5233/console

Resolved now.


Label reviews

Add a Github action to be able to require a custom amount of reviews before allowing a PR to be merged. It is currently impossible to make it require a specific member of a team to have a review in it, but should still be helpful for some labels.

It's merged, but will require batch-updating all repos to link to this file unfortunately

It's merged, but will require batch-updating all repos to link to this file unfortunately

We generally only really need it on the high traffic repos, so that's at least a subset of them 😎


Improve layout switching in GridView

@yaichenbaum with the animations when switching from datagrid to tilesview I see items with the wring icon (e.g files with a folder icon)

@yaichenbaum with the animations when switching from datagrid to tilesview I see items with the wring icon (e.g files with a folder icon)

@yaichenbaum with the animations when switching from datagrid to tilesview I see items with the wrong icon (e.g files with a folder icon) then it fades to the correct one

Do you think this can be fixed by only showing the "add item" animation?

@yaichenbaum with the animations when switching from datagrid to tilesview I see items with the wrong icon (e.g files with a folder icon) then it fades to the correct one

Do you think this can be fixed by only showing the "add item" animation?

Perhaps I'd just wait to add animations, when switching layout there's an ugly moment in which you see a gray background to the items. We'd probably need to fix that anyway before thing to animations.

Perhaps I'd just wait to add animations, when switching layout there's an ugly moment in which you see a gray background to the items. We'd probably need to fix that anyway before thing to animations.

That odd refresh, perhaps you could have a placeholder icon until the grid item content has loaded

That odd refresh, perhaps you could have a placeholder icon until the grid item content has loaded

@yaichenbaum sorry this came out bigger than I thought.
Switching layout mode or gridview size doesn't trigger a refresh anymore even between Datagrid and TilesView

@gave92 Amazing job!

@gave92 Amazing job!


For some measure there is no templated id in the device order ACT for patients

For measure id CMS108,CMS114,CMS190, some of the patients have device order tag which do not have any templateid in the cypress data; due to this the QRDA files are not consumed in our environment.
Please find attached the patients files
2_8 N_N VTE.txt
3_11 N_N VTE.txt

Any update on this ticket?

Hi,
This is actually intentional. The QRDA spec does not allow for Device Order - Not Done, so this is a workaround until the spec issue can be resolved.
For more information please see:
https://jira.oncprojectracking.org/browse/QRDA-176
http://www.hl7.org/dstucomments/showdetail_comment.cfm?commentid=696
Thanks,
Dave Czulada


Add instructions on how to get other versions

I would be nice to have a link to the source of all versions from remarkable itself.
Like, how to get it for the latest hack compatible version <IP_ADDRESS>?
Btw, thanks for doing all this. :D

You can always try to play around with the URLs by replacing the version numbers in them with the version you want.

Hope you don't mind me plugging this, but I did just that a while ago and now have an auto-updating list of firmwares available here.

As of today May 10, 2023
remarkable-hacks
Latest version supported:
rm1: <IP_ADDRESS>9
https://updates-download.cloud.remarkable.engineering/build/reMarkable%20Device%20Beta/RM110/<IP_ADDRESS>9/<IP_ADDRESS>9_reMarkable-Xdvv3lBmE4-.signed
rm2: <IP_ADDRESS>9
https://updates-download.cloud.remarkable.engineering:443/build/reMarkable%20Device%20Beta/RM110/<IP_ADDRESS>9/<IP_ADDRESS>9_reMarkable2-wVbHkgKisg-.signed


Sidebar footer

How do I keep a sticky footer in the main sidebar (in this case a text input)?
I want everything else to scroll underneath, but I want to the text input to always stay in the same place (static). Are there any helper classes in AdminLTE to achieve this?

Also: is there a way to make something in the sidebar hidden when it's minimized?

There is no helper out of the box that I remember.
You have to do that by yourself, and I think it is easy, with absolute positioning and bottom+left values in you css.
There should be a lot of sample code on google as well.

I think it should be part of template. It is not that easy as you say @rafael-renan-pacheco ... :+1:

Fixed footer for both the sidebar and the main content is planned for a future version of AdminLTE. Thanks for the suggestion!

@rafael-renan-pacheco If it's so easy surely you can provide an example? :stuck_out_tongue_winking_eye:


Affix not working when  is not scrollable

In my web page I have this CSS:
html {
    overflow: hidden;
}
body {
    overflow: auto; // Body has scrollbar
}

Apparently it makes the affix functionality break.
One reason seems to be that the events are registered on the window:
    this.$window = $(window)
      .on('scroll.bs.affix.data-api', $.proxy(this.checkPosition, this))
      .on('click.bs.affix.data-api',  $.proxy(this.checkPositionWithEventLoop, this))

Is there any way to make this work when only the body is scrollable?
(Or more general, when a custom element is scrollable)
I am not sure what are the best practices here, but having the <html> element scroll seems a bit weird to me.
(I use Bootstrap v3.1.1)

Support for v3 has mostly ceased. (See https://github.com/twbs/bootstrap/issues/20631)
Please let us know if this issue affects v4.

Hm...
I don't have v.4 in any project. :(
I will see what I can do...

Closing given v3 status.
Bootstrap 3 is essentially in maintenance mode as we focus on working towards a stable v4. As such, we're only accepting changes to v3's code on a case-by-case basis, usually only for critical bug fixes or docs improvements.
Sorry for the inconvenience, and thanks for the suggestion, but we'll be passing on this change.
<3


Android scanner lost autofocus ability after page switch

Got Page that contains ZXingScannerView, on that page have also a button to navigate to the other page. After return from other page, everything is working except Autofocus. Found that on restoring scanner status with reenabling IsScanning scanner don't pass check for if (!tokenSource.IsCancellationRequested)... bla-bla-bla, enable autofocus.
Solved that with this code added on start of StartScanningAsync method:
        if (tokenSource.IsCancellationRequested)
        {
            tokenSource.Dispose();
            tokenSource = new CancellationTokenSource();
        }

Not sure that this snipped is correct, so please check and fix it:)

I have a similar problem. Using the Forms Version for my Scanner View.
I'm inheritance my Page from ZXingScannerPage. This is all working. But when I got a result and want to scan again after this result there is no autofocus with Android.
This is my code to reactivate the scanning. Maybe I did this wrong. Maybe this is a bug. Don't know.
this.IsScanning = true;

this.IsAnalyzing = true;

 this.AutoFocus();

Thanks!


Audio underrun with simultaneous: 3 sample, 1 sid, 1 opal tracks

Issue reported by user on Discord.
Video of issue from user.

Preliminary experiments with OPAL look promising.
By replacing the call into OPAL Sample() to SampleBuffer() which takes the same fixed point buffer that is passed into the OPALInstruments Render() method and then manually inlining the code that is in the Output()  function called by Sample() and then setting the Opal::Operator::Output() method it call to be forced to be inlined by the compiler using:
__attribute__((always_inline)) inline int16_t  Opal::Operator::Output(...
Gives a total improvement of ~30% !
Eg. Initial unoptimised renders took ~4900us while after the above they now take ~3300 us! (the render numbers tend by upto 100us per each Render() )


[Material-UI] Select broken - modifying event target

Looks like the material-ui/core/Select modifies the target on a native event.
Seems they're also doing it on item click: https://github.com/mui-org/material-ui/blob/cdc4b98b62b43d4e7253f731f2028e45d669acf5/packages/material-ui/src/Select/SelectInput.js#L129
Browsers throw an error since the event is marked read-only.
I noticed there is some work to use non-synthetic events in preact-compat -- is there a way to configure it in certain cases?

I can make the issue there -- didn't realize it was a separate repo.
Out build was using:
    "preact": "^10.0.0",
with the wp alias:
			alias: {
				// preact-compat
				'react': 'preact/compat',
				"react-dom/test-utils": "preact/test-utils",
				'react-dom': 'preact/compat', // Must be below test-utils
				// Not necessary unless you consume a module using `createClass`
				'create-react-class': 'preact/compat/lib/create-react-class',
				// Not necessary unless you consume a module requiring `react-dom-factories`
				'react-dom-factories': 'preact/compat/lib/react-dom-factories',
			},

Closing this issue out -- the bugs are already reported in preact

FYI: The create-react-class and react-dom-factories aliases are not needed anymore. They were only present in React <0.14.


"Add Camera Zoom" does not zoom out

Describe your problem here.
How to make "add camera zoom" event zoom back without needing opponent's notes?
Are you modding a build from source or with Lua?
Lua
What is your build target?
Windows x64
Did you edit anything in this build? If so, mention or summarize your changes.
No response

its called "Add Camera Zoom" so I don't think you can zoom it out

Every time the event is used after the opponent start singing it begins zooming out

use positive decimals to zoom in, and negative decimals to zoom out.

last time this happened to me i just placed a note with a strum time of -5000~ ms


Clock wrap not catered for and other issues from a code read through

In HX711_ADC::startMultiple(unsigned int t) appears the line
if(millis() < startMultipleTimeStamp + startMultipleWaitTime)
which will fail to work as expected if startMultipleTimeStamp + startMultipleWaitTime wraps around the clock. The fix is to work with durations instead of times.
if ( millis() - startMultipleTimeStamp > startMultipleWaitTime)
See https://www.norwegiancreations.com/2018/10/arduino-tutorial-avoiding-the-overflow-issue-when-using-millis-and-micros/
I will create a PR but it may be a few days before I can do that.

Likewise in int HX711_ADC::startMultiple(unsigned int t, bool dotare)
and I suspect a lot of other places!

uint8_t HX711_ADC::conversion24bit()
unsigned long data = 0;
if ((data < 0x000000) || (data > 0xFFFFFF))
the first part can never be true since data is unsigned.

data = data ^ 0x800000; // if the 24th bit is '1', change 24th bit to 0
it will also change a 24th bit of '0' to '1'. Is that intended? I think it is in which case the comment is misleading.

data = data << 1;
if (dout)
{
data++;
}
The first line of that can be written data <<= 1
Depending on how smart the compiler is, data |= 1 may be slightly faster than data++.
I would probably have written this as:
data = (data << 1) | (dout == HIGH ? 1 : 0);
I can't see a value specified for HIGH and LOW in the Arduino docs. If specified to be 1 and 0 then this could be reduced to
data = (data << 1) | dout;

A lot of this, the low/high value code, can be compiled out when not needed and the condition removed from the subtractions.
long HX711_ADC::smoothedData()
{
long data = 0;
long L = 0xFFFFFF;
long H = 0x00;
//for (uint8_t r = 0; r < DATA_SET; r++) {
for (uint8_t r = 0; r < (samplesInUse + IGN_HIGH_SAMPLE + IGN_LOW_SAMPLE); r++)
{
#if IGN_LOW_SAMPLE
if (L > dataSampleSet[r]) L = dataSampleSet[r]; // find lowest value
#endif
#if IGN_HIGH_SAMPLE
if (H < dataSampleSet[r]) H = dataSampleSet[r]; // find highest value
#endif
data += dataSampleSet[r];
}
#if IGN_LOW_SAMPLE
data -= L; //remove lowest value
#endif
#if IGN_HIGH_SAMPLE
data -= H; //remove highest value
#endif
return data;
}

smoothedData()
I am surprised that it does not do the >> divBit

Many thanks Malcolm! All your suggestions is now implemented in 1.2.4


elastic_lb LWRP does not remove nodes and always adds nodes to ELB

The elastic_lb LWRP runs a check to see if the node is currently in the ELB, this check does not currently work.
Lines:
providers/elastic_lb:6
providers/elastic_lb:18
providers/elastic_lb:20
Current Behavior:
When actions de/register run, the checks listed above in lines 6 and 18 always fail. So it will always try to add the node to the ELB with register and will never remove a node with deregister.  converge_by will always claim that the action ran successfully.
The deregister_instances_with_load_balancer method does not exist either. The correct method is deregister_instances_from_load_balancer
http://docs.aws.amazon.com/sdkforruby/api/Aws/ElasticLoadBalancing/Client.html#deregister_instances_from_load_balancer-instance_method
So if the deregister action were to run, it would fail when trying to run this method on line 20.

Fixed in #133 - thanks!


Windows 7 gyp build error

Error log:
node "C:\Program Files\nodist\bin\node_modules\npm\bin\node-gyp-bin\\..\..\node_modules\node-gyp\bin\node-gyp.js" rebuild
'.' is not recognized as an internal or external command, operable program or batch file.
gyp: Call to './utils/has_lib.sh gmpxx' returned exit status 1. while trying to load binding.gyp

hi @moshest i don't have a windows machine to test on at the moment. Ill check back when I do.

OK.
Just for reference: tested on node v0.10 and v0.12.
Full error log from node v0.12:
'.' is not recognized as an internal or external command,
operable program or batch file.
gyp: Call to './utils/has_lib.sh gmpxx' returned exit status 1. while trying to
load binding.gyp
gyp ERR! configure error
gyp ERR! stack Error: `gyp` failed with exit code: 1
gyp ERR! stack     at ChildProcess.onCpExit (C:\Program Files\nodist\bin\node_mo
dules\npm\node_modules\node-gyp\lib\configure.js:340:16)
gyp ERR! stack     at ChildProcess.emit (events.js:110:17)
gyp ERR! stack     at Process.ChildProcess._handle.onexit (child_process.js:1074
:12)
gyp ERR! System Windows_NT 6.1.7601
gyp ERR! command "node" "C:\\Program Files\\nodist\\bin\\node_modules\\npm\\node
_modules\\node-gyp\\bin\\node-gyp.js" "rebuild"
gyp ERR! cwd C:\Users\owner\git\nodejs\Anternet\prototype\node_modules\secp256k1

gyp ERR! node -v v0.12.4
gyp ERR! node-gyp -v v0.13.0
gyp ERR! not ok
npm ERR<EMAIL_ADDRESS>install: `node-gyp rebuild`
npm ERR! Exit status 1

well ./utils/has_lib.sh is a bash script. I'm would assume widows doesn't
have bash.
On Mon, Jun 8, 2015 at 5:24 PM, Moshe Simantov<EMAIL_ADDRESS>wrote:

OK.
Just for reference: tested on node v0.10 and v0.12.
Full error log from node v0.12:
'.' is not recognized as an internal or external command,
operable program or batch file.
gyp: Call to './utils/has_lib.sh gmpxx' returned exit status 1. while trying to
load binding.gyp
gyp ERR! configure error
gyp ERR! stack Error: gyp failed with exit code: 1
gyp ERR! stack     at ChildProcess.onCpExit (C:\Program Files\nodist\bin\node_mo
dules\npm\node_modules\node-gyp\lib\configure.js:340:16)
gyp ERR! stack     at ChildProcess.emit (events.js:110:17)
gyp ERR! stack     at Process.ChildProcess._handle.onexit (child_process.js:1074
:12)
gyp ERR! System Windows_NT 6.1.7601
gyp ERR! command "node" "C:\Program Files\nodist\bin\node_modules\npm\node
_modules\node-gyp\bin\node-gyp.js" "rebuild"
gyp ERR! cwd C:\Users\owner\git\nodejs\Anternet\prototype\node_modules\secp256k1
gyp ERR! node -v v0.12.4
gyp ERR! node-gyp -v v0.13.0
gyp ERR! not ok
npm ERR<EMAIL_ADDRESS>install: node-gyp rebuild
npm ERR! Exit status 1
—
Reply to this email directly or view it on GitHub
https://github.com/wanderer/secp256k1-node/issues/20#issuecomment-110145616
.

so the bash is just to detect whether to complile using gmp or not. If your on windows you probably won't have gmp either.  What happens if you just set this to false?

Got other error:
Building the projects in this solution one at a time. To enable parallel build,
please add the "/m" switch.

   secp256k1.cc
..\secp256k1.cc(5): fatal error C1083: Cannot open include file: './secp256k1-s
rc/include/secp256k1.h': No such file or directory [E:\Users\owner\Downloads\se
cp256k1-node\build\secp256k1.vcxproj]
gyp ERR! build error
gyp ERR! stack Error: `C:\Windows\Microsoft.NET\Framework\v4.0.30319\msbuild.exe
` failed with exit code: 1

Now there is a log of errors like:
          E:\Program Files (x86)\Visual Studio 2012\VC\include\stdint.h(14) : s
  ee declaration of 'uint32_t'
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
3): error C2146: syntax error : missing ';' before identifier 'z0' [C:\Users\ow
ner\Downloads\secp256k1-node\build\secp256k1.vcxproj]
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
3): error C2065: 'z0' : undeclared identifier [C:\Users\owner\Downloads\secp256
k1-node\build\secp256k1.vcxproj]
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
3): error C2065: 'z1' : undeclared identifier [C:\Users\owner\Downloads\secp256
k1-node\build\secp256k1.vcxproj]
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
6): error C2065: 'z0' : undeclared identifier [C:\Users\owner\Downloads\secp256
k1-node\build\secp256k1.vcxproj]
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
6): error C2065: 'z1' : undeclared identifier [C:\Users\owner\Downloads\secp256
k1-node\build\secp256k1.vcxproj]
c:\users\owner\downloads\secp256k1-node\secp256k1-src\src\field_10x26_impl.h(23
9): error C2275: 'uint32_t' : illegal use of this type as an expression [C:\Use
rs\owner\Downloads\secp256k1-node\build\secp256k1.vcxproj]

and more...

If anyone has a window machine and knows how to compile https://github.com/bitcoin/secp256k1 on it please I would love to know/ have help

Installed MSVS 2015 Express and Python 2.7
Added https://github.com/bitcoin/secp256k1 files to "secp256k1-src" directory
Edited "bindings.gyp" line 5-47 to:
    },
    "sources": [
      "functions.cc",
      "util.cc",
      "secp256k1.cc",
      "secp256k1-src/src/secp256k1.c",
      "secp256k1-src/src/ecdsa.h",
      "secp256k1-src/src/ecdsa_impl.h",
      "secp256k1-src/src/eckey.h",
      "secp256k1-src/src/eckey_impl.h",
      "secp256k1-src/src/ecmult_const.h",
      "secp256k1-src/src/ecmult_const_impl.h",
      "secp256k1-src/src/ecmult_gen.h",
      "secp256k1-src/src/ecmult_gen_impl.h",
      "secp256k1-src/src/ecmult.h",
      "secp256k1-src/src/ecmult_impl.h",
      "secp256k1-src/src/field_10x26.h",
      "secp256k1-src/src/field_10x26_impl.h",
      "secp256k1-src/src/field_5x52.h",
      "secp256k1-src/src/field_5x52_impl.h",
      "secp256k1-src/src/field_5x52_int128_impl.h",
      "secp256k1-src/src/field_5x52_asm_impl.h",
      "secp256k1-src/src/field.h",
      "secp256k1-src/src/field_impl.h",
      "secp256k1-src/src/group.h",
      "secp256k1-src/src/group_impl.h",
      "secp256k1-src/src/num.h",
      "secp256k1-src/src/num_impl.h",
      "secp256k1-src/src/num_gmp.h",
      "secp256k1-src/src/num_gmp_impl.h",
      "secp256k1-src/src/scalar_4x64.h",
      "secp256k1-src/src/scalar_4x64_impl.h",
      "secp256k1-src/src/scalar_8x32.h",
      "secp256k1-src/src/scalar_8x32_impl.h",
      "secp256k1-src/src/scalar.h",
      "secp256k1-src/src/scalar_impl.h",
      "secp256k1-src/src/util.h",
      "secp256k1-src/src/modules/schnorr/main_impl.h",
      "secp256k1-src/src/modules/schnorr/schnorr_impl.h",
      "secp256k1-src/src/modules/schnorr/schnorr.h",
      "secp256k1-src/src/modules/ecdh/main_impl.h",
      "secp256k1-src/src/modules/recovery/main_impl.h"

Edited "functions.cc" line 4-5 to:
#include "async.h"

Edited "util.cc" line 5 to:

Edited "util.h" line 7 and 8 to:
#include "secp256k1-src/include/secp256k1_recovery.h"

Edited "async.h" line 6 to:

Edited "secp256k1.cc" line 4-5 to:
#include "functions.h"

Got:
th\node_modules\secp256k1\build\secp256k1.vcxproj]
..\functions.cc(182): error C3861: 'secp256k1_ec_privkey_export': identifier not found [C:\Users\gunars\Documents\bitau
th\node_modules\secp256k1\build\secp256k1.vcxproj]
``` so I edited "functions.cc" corresponding lines to:
int results = 0;

Got bunch of warnings and:
```LINK : fatal error LNK1181: cannot open input file 'C:\OpenSSL-Win32\lib\libeay32.lib' [C:\Users\gunars\Documents\bitau
th\node_modules\secp256k1\build\secp256k1.vcxproj]```
so I downloaded OpenSSL from https://code.google.com/p/openssl-for-windows/downloads/detail?name=openssl-0.9.8k_WIN32.zip

And compiled successfully adding npm parameter --msvs_version=2015

Now how do I fix secp256k1_ec_privkey_import/secp256k1_ec_privkey_export error?

@gunarssimkuns thanks for working on this! re: the secp256k1_ec_privkey_import/secp256k1_ec_privkey_export idk but stackoverflow suggests that it could be a problem with the header order. Maybe check that?

Using search I found out that secp256k1_ec_privkey_import/secp256k1_ec_privkey_export functions are not defined anywhere in the sources, maybe I am missing something?
The only function I found was "secp256k1_ec_privkey_import_der()" in "secp256k1-src\contrib\lax_der_privatekey_parsing.h" file.

@gunarssimkuns  It here and here Maybe you submodule is at a different commit?

Yes, thank you now it compiles without errors.
I was using a different commit, so my "secp256k1/include/secp256k1.h" file looked a lot different.

@gunarssimkuns if you got this to work, could you send in a PR with the changes you made?

Just setting with_gimp=false will make it compilable on Windows, with no other changes.
Download or compile OpenSSL in C:\OpenSSL-Win32 or OpenSSL-Win64, or add --openssl_root=[path] to point to an openssl installation somewhere else (it should have lib/libeay32.lib in it)
  "variables": {
    "conditions": [
      [
        "OS=='win'",
        {
            "with_gmp%": "false"
        },
        {
            "with_gmp%": "<!(utils/has_lib.sh gmpxx && utils/has_lib.sh gmp)"
        }
      ]
    ]
  },

@Maarten88 I tried following what you put above, but I'm still receiving errors on Windows 8.1 64bit. Mind taking a look? https://gist.github.com/anonymous/3416fe67808025e001e6

Here's what I had to do to get it to install on Windows: https://github.com/cryptocoinjs/secp256k1-node/pull/73

@moshest @gunarssimkuns @Maarten88 please check version 3.0.1!

Thank you. I no longer use Windows :)

@fanatid Shouldn't this be closed given #73 was merged?

@axic yeah, I think we can close this issue.


Technic-less support?

I tried integration branch of a fork, doesn't work without technic. Can't add an issue to a fork, so adding there.
Error:
ModError: Failed to load and run script from /home/infinitecoder/.minetest/mods/microexpansion/init.lua:
...r/.minetest/mods/microexpansion/modules/network/ctrl.lua:362: attempt to call global 'no_technic' (a nil value)
stack traceback:
	...r/.minetest/mods/microexpansion/modules/network/ctrl.lua:362: in main chunk
	[C]: in function 'dofile'
	...r/.minetest/mods/microexpansion/modules/network/init.lua:202: in main chunk
	[C]: in function 'dofile'
	/home/infinitecoder/.minetest/mods/microexpansion/init.lua:58: in function 'require_module'
	...etest/mods/microexpansion/modules/item_transfer/init.lua:5: in main chunk
	[C]: in function 'dofile'
	/home/infinitecoder/.minetest/mods/microexpansion/init.lua:58: in function 'load_module'
	/home/infinitecoder/.minetest/mods/microexpansion/init.lua:82: in main chunk
Check debug.txt for details.

Removing the no_technic() line in the ctrl.lua does seem to fix the issue, but, like with technic, inteface/controllers say "no power", when I look at them it also says "no network"

Oh, so there is no way to enable controller without mesecons...

I guess I should be writing all of that in the PR


Certain interactive commands complete with 'NoneType' object has no attribute 'init_progress'

Install Method: apt-get
CLI Version:
azure-cli (2.0.24)

acr (2.0.18)
acs (2.0.23)
advisor (0.1.1)
appservice (0.1.23)
backup (1.0.4)
batch (3.1.8)
batchai (0.1.4)
billing (0.1.7)
cdn (0.0.11)
cloud (2.0.11)
cognitiveservices (0.1.10)
command-modules-nspkg (2.0.1)
configure (2.0.13)
consumption (0.2.1)
container (0.1.16)
core (2.0.24)
cosmosdb (0.1.16)
dla (0.0.16)
dls (0.0.19)
eventgrid (0.1.7)
extension (0.0.7)
feedback (2.0.7)
find (0.2.8)
interactive (0.3.12)
iot (0.1.16)
keyvault (2.0.16)
lab (0.0.14)
monitor (0.0.14)
network (2.0.20)
nspkg (3.0.1)
profile (2.0.17)
rdbms (0.0.10)
redis (0.2.11)
reservations (0.1.1)
resource (2.0.20)
role (2.0.16)
servicefabric (0.0.8)
sql (2.0.18)
storage (2.0.22)
vm (2.0.23)

Python location '/opt/az/bin/python3'
Extensions directory '/home/tda/.azure/cliextensions'

Python (Linux) 3.6.1 (default, Jan  5 2018, 21:18:08)
[GCC 4.8.4]

OS Version:
Distributor ID: Ubuntu
Description:    Ubuntu 16.04.3 LTS
Release:        16.04
Codename:       xenial

Shell: bash
Issue:

az interactive. Output:

az>> Command: provider list not in Command Table
Command: sql db op cancel not in Command Table
Command: storage account generate-sas not in Command Table

Hit enter and create a new group:

az>> group create -n test -l westeurope -o json

Try and delete the group:

az>> group delete -n test -y
'NoneType' object has no attribute 'init_progress'
Traceback (most recent call last):
  File "/opt/az/lib/python3.6/site-packages/knack/cli.py", line 193, in invoke
    cmd_result = self.invocation.execute(args)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 319, in execute
    six.reraise(*sys.exc_info())
  File "/opt/az/lib/python3.6/site-packages/six.py", line 693, in reraise
    raise value
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 303, in execute
    result = LongRunningOperation(self.cli_ctx, 'Starting {}'.format(cmd.name))(result)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 438, in __call__
    self.cli_ctx.get_progress_controller().begin()
  File "/opt/az/lib/python3.6/site-packages/azclishell/app.py", line 679, in progress_patch
    self.cli_ctx.progress_controller.init_progress(ShellProgressView())
AttributeError: 'NoneType' object has no attribute 'init_progress'
'int' object has no attribute 'result'
Traceback (most recent call last):
  File "/opt/az/lib/python3.6/site-packages/azclishell/app.py", line 660, in cli_execute
    if result and result.result is not None:
AttributeError: 'int' object has no attribute 'result'
az>>

Additional Information:
The group is deleted but the it exits immediately without waiting for the completion (without --no-wait)
The intellisence / autocompletion does not seem to work either

I have the same problem running some commands like creation of vm(ss):
azure-cli (2.0.27)

acr (2.0.21)
acs (2.0.26)
advisor (0.1.2)
appservice (0.1.26)
backup (1.0.6)
batch (3.1.10)
batchai (0.1.5)
billing (0.1.7)
cdn (0.0.13)
cloud (2.0.12)
cognitiveservices (0.1.10)
command-modules-nspkg (2.0.1)
configure (2.0.14)
consumption (0.2.1)
container (0.1.18)
core (2.0.27)
cosmosdb (0.1.19)
dla (0.0.18)
dls (0.0.19)
eventgrid (0.1.10)
extension (0.0.9)
feedback (2.1.0)
find (0.2.8)
interactive (0.3.16)
iot (0.1.17)
keyvault (2.0.18)
lab (0.0.17)
monitor (0.1.2)
network (2.0.23)
nspkg (3.0.1)
profile (2.0.19)
rdbms (0.0.12)
redis (0.2.11)
reservations (0.1.1)
resource (2.0.23)
role (2.0.19)
servicefabric (0.0.10)
sql (2.0.21)
storage (2.0.25)
vm (2.0.26)

Python location '/home/paraita/lib/azure-cli/bin/python'
Extensions directory '/home/paraita/.azure/cliextensions'

Python (Linux) 3.6.4 (default, Jan  5 2018, 02:35:40)
[GCC 7.2.1 20171224]

Legal docs and information: aka.ms/AzureCliLegal

I'm running Archlinux, the cli has been installed with:
curl -L https://aka.ms/InstallAzureCli | bash

The commands works but I kinda lose the progress character animation.


Update change-the-phone-numbers-on-your-audio-conferencing-bridge.md

https://github.com/MicrosoftDocs/OfficeDocs-SkypeForBusiness/issues/4296
Fixed typo

@JohanFreelancer9 Copy editing is needed for this PR. Thanks.

@tonysmit PR has been copyedited and is ready for final review, could you please check and merge? Thanks!


Unicode gets unescaped

The obfuscator seems to unescape escaped unicode in strings. For example, consider the following input javascript:
console.log("\ud83d\ude03");
console.log("😃");

Expected Behavior

I expect the unicode escape sequences to be preserved. Something like this is expected:
console['log']('\ud83d\ude03');console['log']('😃');

Current Behavior

Escaped characters are unescaped. For the code above, the default obfuscation options produce:
console['log']('😃');console['log']('😃');

Notice the smiley faces appear as unicode characters, that is, they are no longer escaped. Note that if the "Escape Unicode Sequence" option is enabled then that does not happen and instead we get:
console['\x6c\x6f\x67']('\ud83d\ude03');console['\x6c\x6f\x67']('\ud83d\ude03');

However, from my understanding and documentation, this option is not about unescaping unicode, it is about escaping unicode (or escaping everything in general).
Steps to Reproduce (for bugs)
Obfuscate the above code using default configuration on https://obfuscator.io/ .
Your Environment

Used https://obfuscator.io/ .

So I tried a few attempts to fix it. Without any successful result. Every time something breaks. So I keep this issue open but it's very possible that I won't fix this.
If someone can help me with this issue, here is a branch with the changes but with failing tests.
https://github.com/javascript-obfuscator/javascript-obfuscator/pull/775/files

This becomes a serious bug in the following case:
const reStr = '\xc0-\xd6\xd8-\xf6\xf8-\u02c1\u02c6-\u02d1'; // regexp ranges
const re = new RegExp('['+reStr+']');

In this case the regex is incorrect.
The example is taken from real life, see https://github.com/acornjs/acorn/blob/master/acorn/src/generated/nonASCIIidentifierStartChars.js