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Results 61 - 70 of 120 for _output_shapes (0.19 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
// dimensions. SmallVector<int64_t> output_shape(output_tensor_rank); for (int i = 0; i < output_tensor_rank; i++) { if (collapsed_dims.contains(i)) { // The collapsed dimension's size should have been 1, so it restores the // dimension with size 1. output_shape[i] = 1; } else { output_shape[i] = *shape_itr; shape_itr++; } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_util.cc
std::vector<PartialTensorShape> output_shapes; std::transform(iter.second.begin(), iter.second.end(), std::back_inserter(output_shapes), [](const InferredShape& inferred_shape) { return inferred_shape.shape; }); Node* n = node_name_index[iter.first]; n->AddAttr(kXlaInferredShapesAttrName, output_shapes); } return absl::OkStatus();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 15.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_device_index_selector.mlir
%1 = "tf.DeviceIndex"() {device = "", device_names = ["CPU", "GPU"]} : () -> tensor<i32> %4 = "tf.Case"(%1, %arg0, %arg1) {branches = [@sub, @add], output_shapes = [#tf_type.shape<>], is_stateless = false} : (tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<f32> func.return %0, %4 : tensor<i32>, tensor<f32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/pin-ops-with-side-effects.mlir
func.func @tf_if_gets_control_node(%arg0: tensor<1xi1>)->() { "tf.If"(%arg0) {_lower_using_switch_merge = true, _read_only_resource_inputs = [], device = "", else_branch = @noop, is_stateless = false, output_shapes = [#tf_type.shape<>], then_branch = @noop} : (tensor<1xi1>) -> () func.return } // CHECK-NEXT: %[[CONTROL:.*]] = tfl.control_node controls "tf.If" // CHECK-NEXT: return // CHECK-LABEL: @tfl_if_gets_control_node
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 17 10:45:19 UTC 2022 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/func_list_attr.mlir
// CHECK-NEXT: } // CHECK-NEXT: } // CHECK-NEXT: } // CHECK: } %1:2 = tf_executor.island wraps "tf.Case"(%0#0) {Tin = [], Tout = ["tfdtype$DT_FLOAT"], branches = [@foo, @bar], device = "", output_shapes = [], is_stateless = false} : (tensor<i32>) -> tensor<*xf32> loc("Case") tf_executor.fetch } func.return } // CHECK-DAG: name: "foo" func.func @foo() -> tensor<10xf32> { %0 = tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/perception_ops_utils_test.cc
mlir::Builder* builder, const SmallVector<int64_t, 4>& input_shape, const SmallVector<int64_t, 4>& output_shape) { auto input_type = RankedTensorType::get(input_shape, builder->getF32Type()); auto indices_type = RankedTensorType::get(input_shape, builder->getI64Type()); auto output_type = RankedTensorType::get(output_shape, builder->getF32Type()); SmallVector<mlir::Type, 2> input_types{input_type, indices_type};
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Sep 29 21:02:21 UTC 2022 - 7.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/analyze-variables.mlir
output_shapes = [#tf_type.shape<?>], output_types = [!tf_type.string]} : (tensor<*x!tf_type.variant>, tensor<i64>) -> tensor<!tf_type.variant> %1 = "tf.ReduceDataset"(%0, %cst_1, %arg0) { Targuments = [!tf_type.resource], Tstate = [i32], device = "", f = @__reduce_func, f._tf_data_function = true, output_shapes = [#tf_type.shape<>],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 09 11:49:28 UTC 2022 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_xla_attribute_utils.cc
SmallVector<int64_t> output_shape(input_shape.getShape().begin(), input_shape.getShape().end()); for (int i : spatial_dims) { output_shape[i] += padding_values[2 * i] + padding_values[2 * i + 1]; } return builder.create<TF::PadV2Op>( loc, RankedTensorType::get(output_shape, builder.getI8Type()), input, temp_padding,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/xla_sharding_util.cc
const mlir::TensorType cluster_func_output_type, const xla::OpSharding& output_sharding, mlir::Type* tiled_logical_computation_type) { const auto output_shape = cluster_func_output_type.getShape(); auto new_output_shape = llvm::to_vector<4>(output_shape); auto dimension_to_splits_map = GetDimensionIndicesAndNumSplitsFromSharding(output_sharding); if (!dimension_to_splits_map.ok()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 21:28:13 UTC 2024 - 34K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/fuse-tftext.mlir
%17 = "tf.If"(%2, %2, %13, %13) {_lower_using_switch_merge = true, _read_only_resource_inputs = [], device = "", else_branch = @WhitespaceTokenize_RaggedConcat_assert_equal_1_Assert_AssertGuard_false_3210, is_stateless = false, output_shapes = [#tf_type.shape<>], then_branch = @WhitespaceTokenize_RaggedConcat_assert_equal_1_Assert_AssertGuard_true_3200} : (tensor<i1>, tensor<i1>, tensor<i64>, tensor<i64>) -> tensor<i1>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 460.3K bytes - Viewed (0)