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Results 1 - 2 of 2 for conv2d_backprop_filter (0.26 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
func.return %result : tensor<2x8x8x8x1xf32> } // ----- // CHECK-LABEL: @conv2d_backprop_filter func.func @conv2d_backprop_filter( %input: tensor<100x28x28x1xf32>, %out_backprop: tensor<100x26x26x32xf32> ) -> tensor<3x3x1x32xf32> { // CHECK: %[[RESULT:.*]] = mhlo.convolution(%arg0, %arg1)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
std::vector<int64_t> explicit_paddings; if (padding == tensorflow::Padding::EXPLICIT) { // EXPLICIT padding mode and the associated attribute is limited to // Conv2DBackpropFilter. So, fetch attribute by identifier instead of the // op.explicit_paddings() attribute getter. ArrayRef<Attribute> explicit_paddings_attr =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)