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tensorflow/compiler/mlir/tensorflow/tests/replicate_invariant_op_hoisting.mlir
} func.return } // CHECK: %[[SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_0]]) // CHECK: %[[OP_A:[0-9]*]] = "tf.opA"(%[[SHAPE]]) // CHECK: %[[OP_B:[0-9]*]] = "tf.opB"(%[[SHAPE]], %[[OP_A]]) // CHECK: tf_device.replicate // CHECK: tf_device.return %[[SHAPE]], %[[OP_A]], %[[OP_B]] // CHECK-LABEL: func @nested_ops
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:59:10 UTC 2023 - 11.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.cc
if (pack_axis < 0) { pack_axis += rank; } // Concat out shape. for (int i = 0; i < rank; ++i) { int64_t dim_size = input_type.getDimSize(i); if (i == pack_axis) { dim_size *= count; } concat_out_shape.push_back(dim_size); } // Pack out shape. int j = 0; for (int i = 0; i < rank + 1; ++i) { if (i == pack_axis) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 25.4K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad_test.cc
xs.push_back(Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape))); auto y = AddN(scope_, xs); RunTest(xs, {shape, shape, shape}, {y}, {shape}); } TEST_F(NaryGradTest, Add) { TensorShape x1_shape({3, 2, 5}); TensorShape x2_shape({2, 5}); auto x1 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x1_shape)); auto x2 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x2_shape));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 36K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unidirectional_sequence_lstm.mlir
// CHECK-NEXT: }, { // CHECK-NEXT: shape: [ 0 ], // CHECK-NEXT: name: "input_to_input_intermediate", // CHECK-NEXT: has_rank: true // CHECK-NEXT: }, { // CHECK-NEXT: shape: [ 0 ], // CHECK-NEXT: name: "input_to_forget_intermediate", // CHECK-NEXT: has_rank: true // CHECK-NEXT: }, { // CHECK-NEXT: shape: [ 0 ], // CHECK-NEXT: name: "input_to_cell_intermediate",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 11.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm.mlir
// CHECK-NEXT: subgraphs: [ { // CHECK-NEXT: tensors: [ { // CHECK-NEXT: shape: [ 1, 4 ], // CHECK-NEXT: buffer: 1, // CHECK-NEXT: name: "arg0", // CHECK-NEXT: quantization: { // CHECK-EMPTY: // CHECK-NEXT: }, // CHECK-NEXT: has_rank: true // CHECK-NEXT: }, { // CHECK-NEXT: shape: [ 4, 4 ], // CHECK-NEXT: buffer: 2, // CHECK-NEXT: name: "arg1",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm_asym_attr.mlir
// CHECK-NEXT: subgraphs: [ { // CHECK-NEXT: tensors: [ { // CHECK-NEXT: shape: [ 1, 4 ], // CHECK-NEXT: buffer: 1, // CHECK-NEXT: name: "arg0", // CHECK-NEXT: quantization: { // CHECK-EMPTY: // CHECK-NEXT: }, // CHECK-NEXT: has_rank: true // CHECK-NEXT: }, { // CHECK-NEXT: shape: [ 4, 4 ], // CHECK-NEXT: buffer: 2, // CHECK-NEXT: name: "arg1",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.h
return transposed_type; } // Returns shape of a ranked tensor. // Precondition: output_val's is ranked tensor. // Returns a truncated shape when `truncate` is set to true. inline DenseElementsAttr GetShape(Value output_val, bool truncate = false) { auto output_shape = output_val.getType().dyn_cast<ShapedType>().getShape(); SmallVector<int32_t> shape; shape.reserve(output_shape.size());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0) -
src/test/java/jcifs/tests/FileLocationTest.java
private String server; private String share; private String path; private int pathConsumed; /** * */ public TestDfsReferral ( String server, String share, String path, int pathConsumed ) { this.server = server; this.share = share; this.path = path; this.pathConsumed = pathConsumed;
Registered: Wed Jun 12 15:45:55 UTC 2024 - Last Modified: Wed Jan 08 13:16:07 UTC 2020 - 23K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
// Extracts shape from XlaArgument as TensorShape. If shape is a xla::Shape, // that is converted to a TensorShape. absl::StatusOr<TensorShape> GetTensorShapeFromXlaArgument( const XlaArgument& arg) { if (absl::holds_alternative<xla::Shape>(arg.shape)) { TensorShape arg_shape; TF_RETURN_IF_ERROR( XLAShapeToTensorShape(std::get<xla::Shape>(arg.shape), &arg_shape)); return arg_shape;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 45.3K bytes - Viewed (0) -
tensorflow/compiler/jit/shape_inference.cc
// Merge node causes a loop so we remove NextIteration->Merge edge before // performing shape inference. But removing those edges also prevents us // from inferring output shape for Merge node (we need shapes for all its // inputs). // For loop invariant resource input's Merge node, we set output resource // shape as Enter node's resource shape. // TODO(b/129367850): clean this up.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 00:41:19 UTC 2024 - 13K bytes - Viewed (0)