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Results 1 - 10 of 17 for conv2d_backprop_filter (0.39 sec)
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tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
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/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/tensorflow/tests/layout_optimization_layout_assignment_gpu_cc_60.mlir
%input: tensor<1x28x28x64xf16>, %filter_size: tensor<4xi32>, %out_backprop: tensor<1x28x28x64xf16> ) -> tensor<1x1x64x64xf16> { // CHECK: "tf.Conv2DBackpropFilter" // CHECK-SAME: data_format = "NCHW" %0 = "tf.Conv2DBackpropFilter"(%input, %filter_size, %out_backprop) { data_format = "NHWC", padding = "VALID", strides = [1, 1, 1, 1]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 21 08:41:18 UTC 2022 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_gpu_cc_70.mlir
%input: tensor<1x28x28x64xf32>, %filter_size: tensor<4xi32>, %out_backprop: tensor<1x28x28x64xf32> ) -> tensor<1x1x64x64xf32> { // CHECK: "tf.Conv2DBackpropFilter" // CHECK-SAME: data_format = "NCHW" %0 = "tf.Conv2DBackpropFilter"(%input, %filter_size, %out_backprop) { data_format = "NHWC", padding = "VALID", strides = [1, 1, 1, 1]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 21 08:41:18 UTC 2022 - 8.5K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad.cc
.UseCudnnOnGpu(use_cudnn_on_gpu)); grad_outputs->push_back(dx_1); auto dx_2 = Conv2DBackpropFilter(scope, op.input(0), Shape(scope, op.input(1)), grad_inputs[0], strides, padding, Conv2DBackpropFilter::DataFormat(data_format) .UseCudnnOnGpu(use_cudnn_on_gpu)); grad_outputs->push_back(dx_2);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 27 23:34:33 UTC 2022 - 24.5K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main_graph_mode.golden_summary
VarHandleOp 435 _Retval 2 cluster 0 size 2178 Add 17 AddN 72 ArgMax 1 AssignAddVariableOp 1 AssignSubVariableOp 106 BiasAdd 1 BiasAddGrad 1 Cast 3 Const 357 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 DivNoNan 1 Equal 1 FusedBatchNorm 53 FusedBatchNormGrad 53 Identity 2 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 164 Pad 1 ReadVariableOp 646
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 740 bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main.golden_summary
ReadVariableOp 2 Switch 1 _Arg 435 _Retval 2 cluster 0 size 1910 Add 16 AddN 71 ArgMax 1 AssignAddVariableOp 1 BiasAdd 1 BiasAddGrad 1 Cast 115 Const 407 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 Equal 1 FusedBatchNormGradV2 53 FusedBatchNormV2 53 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 218 Pad 2 ReadVariableOp 538 Relu 49 ReluGrad 49
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 874 bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main.pbtxt
attr { key: "T" value { type: DT_FLOAT } } } node { name: "training/LossScaleOptimizer/gradients/res5c_branch2c_1/Conv2D_grad/Conv2DBackpropFilter" op: "Conv2DBackpropFilter" input: "activation_47_1/Relu" input: "ConstantFolding/training/LossScaleOptimizer/gradients/res5c_branch2c_1/Conv2D_grad/ShapeN-matshapes-1"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 30 02:52:54 UTC 2019 - 1.3M bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
// CHECK: %[[IN_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg0, %[[ARG_PERM]]) // CHECK: %[[OUT_BP_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg2, %[[ARG_PERM]]) // CHECK: %[[CONV2D_BACKPROP:[0-9]*]] = "tf.Conv2DBackpropFilter" // CHECK-SAME: (%[[IN_TRANSPOSE]], %[[FILTER_PERM]], %[[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) -
tensorflow/compiler/jit/tests/keras_imagenet_main_graph_mode.pbtxt
} attr { key: "use_cudnn_on_gpu" value { b: true } } } node { name: "training/SGD/gradients/res5c_branch2c_1/Conv2D_grad/Conv2DBackpropFilter" op: "Conv2DBackpropFilter" input: "activation_47_1/Relu" input: "ConstantFolding/training/SGD/gradients/res5c_branch2c_1/Conv2D_grad/ShapeN-matshapes-1"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 30 02:52:54 UTC 2019 - 1.1M bytes - Viewed (0)