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RELEASE.md
* Fixes a missing validation which causes denial of service via `Conv3DBackpropFilterV2` ([CVE-2022-29196](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-29196)) * Fixes a `CHECK` failure in depthwise ops via overflows ([CVE-2021-41197](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-41197))
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
const int64_t filter_channels = GetDimSize(filter_ty, num_spatial_dims); // TensorFlow convolution op verifies that the number of input channels is // divisible by the number of filter channels. // For depthwise convolution the feature_group_count argument would be set // to the input feature dimension. const int64_t feature_group_count = depthwise_conv ? input_channels : input_channels / filter_channels;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
); TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>; } def TF_DepthwiseConv2dNativeOp : TF_Op<"DepthwiseConv2dNative", [Pure]> { let summary = [{ Computes a 2-D depthwise convolution given 4-D `input` and `filter` tensors. }]; let description = [{ Given an input tensor of shape `[batch, in_height, in_width, in_channels]` and a filter / kernel tensor of shape
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)