- Sort Score
- Result 10 results
- Languages All
Results 1 - 3 of 3 for conv2d_backprop_input (0.33 sec)
-
tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
strides = [1, op.get_attr('stride_w'), op.get_attr('stride_h'), 1] padding = op.get_attr('padding') shape_0, shape_1 = tf.shape_n([op.inputs[0], op.inputs[1]]) return [ tf.compat.v1.nn.conv2d_backprop_input( shape_0, op.inputs[1], grad, strides=strides, padding=padding, dilations=dilations, data_format='NHWC'),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 31 20:23:51 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
} // CHECK-LABEL: conv2d_backprop_input_with_add func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> { %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
// CHECK: %[[ARG_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}> // CHECK: %[[OUT_BP_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg2, %[[ARG_PERM]]) // CHECK: %[[CONV2D_BACKPROP:[0-9]*]] = "tf.Conv2DBackpropInput" // CHECK-SAME: (%[[INPUT_PERM]], %arg1, %[[OUT_BP_TRANSPOSE]]) // CHECK-SAME: data_format = "NCHW" // CHECK-SAME: dilations = [1, 4, 2, 3] // CHECK-SAME: explicit_paddings = [1, 2, 7, 8, 3, 4, 5, 6]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9K bytes - Viewed (0)