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Results 1 - 3 of 3 for conv2d_backprop_input (0.35 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir 

      return %result : tensor<?x512x512x1xf32>
}

// -----

// CHECK-LABEL: @conv2d_backprop_input
func.func @conv2d_backprop_input(
    %filter: tensor<3x3x1x32xf32>,
    %out_backprop: tensor<100x26x26x32xf32>
  ) -> tensor<100x28x28x1xf32> {
    // CHECK: %[[REV_FILTER:.*]] = "mhlo.reverse"(%arg0) <{dimensions = dense<[0, 1]> : tensor<2xi64>}>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon May 06 18:46:23 UTC 2024
    - 335.5K bytes
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir 

    // CHECK:            %[[VAL_6:.*]] = "tf.Const"() <{value = dense<[1, 128, 128, 64]> : tensor<4xi32>}> : () -> tensor<4xi32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
    - 340.2K bytes
    - Viewed (0)
  4. github.com/tensorflow/tensorflow

    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
      // Conv2DBackpropInput. 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)
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