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Results 11 - 20 of 79 for RELU (0.04 sec)
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tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_begin.mlir
// CHECK: %[[TANH:[0-9]*]] = "tf.Tanh"(%[[ARG_TRANSPOSE]]) {{.*}} tensor<1x8x4x4xf32> // CHECK: %[[RELU:[0-9]*]] = "tf.Relu"(%[[TANH]]) {{.*}} tensor<1x8x4x4xf32> // CHECK: return %[[RELU]] %0 = "tf.Tanh"(%arg0) : (tensor<1x4x4x8xf32>) -> tensor<1x4x4x8xf32> %1 = "tf.Relu"(%0) : (tensor<1x4x4x8xf32>) -> tensor<1x4x4x8xf32> %2 = "tf.Const"() {value = dense<[0, 3, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions.mlir
} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32> %4 = "tf.BiasAdd"(%3, %cst) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32> %5 = "tf.Relu"(%4) {device = ""} : (tensor<*xf32>) -> tensor<*xf32> %6 = "tf.Conv2D"(%arg0, %arg1) { data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
// CHECK-SAME: f = @composite_conv3d_fn_1}> // CHECK-NOT: {_tfl_quant_trait = "fully_quantizable" // CHECK: %[[RELU:.*]] = "tf.Relu"(%[[PARTITIONEDCALL_0]]) // CHECK: return %[[RELU]] // CHECK-LABEL: private @composite_conv3d_fn_1 // WEIGHTONLY-DAG: %[[CST:.*]] = "tf.Const"() {{.*}} : () -> tensor<2x3x3x3x2xf32> // WEIGHTONLY: %[[PARTITIONEDCALL_0:.*]] = "tf.PartitionedCall"(%arg0, %[[CST]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/nn_grad_test.cc
using tensorflow::TF_StatusPtr; Status ReluModel(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { return ops::Relu(ctx, inputs[0], &outputs[0], "Relu"); } Status SparseSoftmaxCrossEntropyWithLogitsModel( AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 13:53:47 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_uniform_quantized.mlir
parameters[ {"quantized_ops": ["${main_op}", "BiasAdd"], "act_func": "internal_requantize_no_activation_fn", "output_type": "!tf_type.qint8"}, {"quantized_ops": ["${main_op}", "BiasAdd", "Relu"], "act_func": "internal_requantize_and_relu_fn", "output_type": "!tf_type.qint8"}, {"quantized_ops": ["${main_op}", "BiasAdd", "Relu6"], "act_func": "internal_requantize_and_relu6_fn", "output_type": "!tf_type.qint8"}, ]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 19.3K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass_test.cc
Node* b = ops::UnaryOp("Relu", a, builder.opts().WithName("B")); Node* c = ops::UnaryOp("Relu", b, builder.opts().WithName("C")); Node* d = ops::UnaryOp("UncompilableUnary", c, builder.opts().WithName("D")); Node* e = ops::UnaryOp("Relu", d, builder.opts().WithName("E")); ops::UnaryOp("Relu", e, builder.opts().WithName("F"));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 10:11:10 UTC 2024 - 79.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_end.mlir
// CHECK: %[[TANH:[0-9]*]] = "tf.Tanh"(%arg0) {{.*}} tensor<1x4x4x8xf32> // CHECK: %[[RELU:[0-9]*]] = "tf.Relu"(%[[TANH]]) {{.*}} tensor<1x4x4x8xf32> // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%[[RELU]], %[[RES_PERM]]) // CHECK: return %[[RES_TRANSPOSE]] %0 = "tf.Const"() {value = dense<[0, 3, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/svdf_v2.mlir
// CHECK-NEXT: outputs: [ 5 ], // CHECK-NEXT: builtin_options_type: SVDFOptions, // CHECK-NEXT: builtin_options: { // CHECK-NEXT: rank: 2, // CHECK-NEXT: fused_activation_function: RELU // CHECK-NEXT: } // CHECK-NEXT: } ], // CHECK-NEXT: name: "main" // CHECK-NEXT: } ], // CHECK-NEXT: description: "MLIR Converted.", // CHECK-NEXT: buffers: [ { // CHECK-EMPTY:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/svdf.mlir
// CHECK-NEXT: outputs: [ 5 ], // CHECK-NEXT: builtin_options_type: SVDFOptions, // CHECK-NEXT: builtin_options: { // CHECK-NEXT: rank: 2, // CHECK-NEXT: fused_activation_function: RELU // CHECK-NEXT: } // CHECK-NEXT: } ], // CHECK-NEXT: name: "main" // CHECK-NEXT: } ], // CHECK-NEXT: description: "MLIR Converted.", // CHECK-NEXT: buffers: [ { // CHECK-EMPTY:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main_graph_mode.golden_summary
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 Relu 49 ReluGrad 49 Reshape 2 ResourceApplyKerasMomentum 161 ShapeN 50 Softmax 1 SparseSoftmaxCrossEntropyWithLogits 1 Square 55 Squeeze 1 Sub 106 Sum 57 Tile 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 740 bytes - Viewed (0)