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manifests/charts/base/crds/crd-all.gen.yaml
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jun 06 21:31:42 UTC 2024 - 671.6K bytes - Viewed (0) -
tests/integration/pilot/testdata/gateway-api-crd.yaml
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu May 09 02:01:51 UTC 2024 - 912.2K bytes - Viewed (0) -
manifests/charts/istiod-remote/templates/crd-all.gen.yaml
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jun 06 21:31:42 UTC 2024 - 671.7K bytes - Viewed (0) -
operator/cmd/mesh/testdata/manifest-generate/output/all_on.golden-show-in-gh-pull-request.yaml
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Wed Jan 10 05:10:03 UTC 2024 - 506.8K bytes - Viewed (0) -
RELEASE.md
StandardizedConv2D(tf.keras.layers.Conv2D): def call(self, inputs): mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True) return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var + 1e-10))` Alternatively, you can override `convolution_op`: `python class StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
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/tensorflow/ir/tf_generated_ops.td
} def TF_SelfAdjointEigV2Op : TF_Op<"SelfAdjointEigV2", [Pure]> { let summary = [{ Computes the eigen decomposition of one or more square self-adjoint matrices. }]; let description = [{ Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
okhttp-idna-mapping-table/src/main/resources/okhttp3/internal/idna/IdnaMappingTable.txt
2F82 ; mapped ; 81E3 # 3.0 KANGXI RADICAL MINISTER 2F83 ; mapped ; 81EA # 3.0 KANGXI RADICAL SELF 2F84 ; mapped ; 81F3 # 3.0 KANGXI RADICAL ARRIVE 2F85 ; mapped ; 81FC # 3.0 KANGXI RADICAL MORTAR
Registered: Sun Jun 16 04:42:17 UTC 2024 - Last Modified: Sat Feb 10 11:25:47 UTC 2024 - 854.1K bytes - Viewed (0)