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Results 21 - 30 of 95 for _output_shapes (0.23 sec)
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tensorflow/compiler/mlir/tf2xla/api/v2/tf_executor_to_graph.cc
(*node_def->mutable_attr())["_handle_dtypes"] = handle_dtypes_attr; (*node_def->mutable_attr())["_handle_shapes"] = handle_shapes_attr; } } TF_RETURN_IF_ERROR( SetShapeAttribute("_output_shapes", arg_type, node_def->mutable_attr())); DataType dtype; TF_RETURN_IF_ERROR(ConvertToDataType(arg_type.getElementType(), &dtype)); AttrValue type_attr; type_attr.set_type(dtype);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 23:04:51 UTC 2024 - 35.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
// the shape inference pass is run early in the pass pipeline, shape inference // during import is not necessary. config.enable_shape_inference = false; // Some graphs may require _output_shapes (an unregistered attribute) // to override shapes. It is unfortunately not always set correctly so only // do it optionally. config.unconditionally_use_set_output_shapes =
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/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK-DAG: [[LINSPACE:%.*]] = chlo.broadcast_add [[MUL]], [[START]] {broadcast_dimensions = array<i64>} // CHECK: return [[LINSPACE]] %0 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "", dtype = i32, value = dense<4> : tensor<i32>} : () -> tensor<i32> %1 = "tf.LinSpace"(%arg0, %arg1, %0) : (tensor<f32>, tensor<f32>, tensor<i32>) -> tensor<4xf32> func.return %1 : tensor<4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
func.func @testUnimplementedOp() -> (tensor<i32>, tensor<i32>) { %0 = arith.constant dense<1> : tensor<i32> %1 = arith.constant dense<2> : tensor<i32> %2 = "tf.Maximum"(%0, %1) {_output_shapes = ["tfshape$"]} : (tensor<i32>, tensor<i32>) -> tensor<i32> %3 = "tf.Minimum"(%0, %1) {random_attr = "hello"} : (tensor<i32>, tensor<i32>) -> tensor<i32> func.return %2, %3: tensor<i32>, tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/name_anonymous_iterators.mlir
func.func private @gives_a_name_to_anonymous_iterators() { // CHECK: "tf.Iterator" // CHECK-SAME: output_shapes{{.*}}200x28x28x1{{.*}}200x10 // CHECK-SAME: output_types = [f32, f32] // CHECK-SAME: shared_name = "_iterator1" %0 = "tf.AnonymousIteratorV3"() {output_shapes = [ #tf_type.shape<200x28x28x1>, #tf_type.shape<200x10>], output_types = [f32, f32]} : () -> tensor<!tf_type.resource>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Oct 14 09:25:38 UTC 2022 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/func_attributes_multiple_callers.mlir
%3 = "tf.RangeDataset"(%0, %1, %2) {device = "/device:CPU:0", output_shapes = [#tf_type.shape<>], output_types = [i64], metadata = ""} : (tensor<i64>, tensor<i64>, tensor<i64>) -> tensor<!tf_type.variant> // CHECK: tfrt_fallback_async.executeop key({{[0-9]+}}) cost({{.*}}) device("/device:CPU:0") "tf.FlatMapDataset"({{.*}}) {Targuments = [], metadata = "", output_shapes = [#corert.shape<>], output_types = [i64]} {f = "funcB"} : 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 17 20:57:36 UTC 2022 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/func_attributes.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Nov 16 18:13:18 UTC 2022 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_data_fuse_map_and_batch.mlir
%3 = "tf.TensorSliceDataset"(%2) {device = "", output_shapes = [#tf_type.shape<>], metadata = ""} : (tensor<3xi32>) -> tensor<*x!tf_type.variant> // CHECK: "tf.MapAndBatchDataset"(%[[TSLICE]], %[[BSIZE:.*]], %[[NPC]] // CHECK-SAME: f = @"__inference_Dataset_map_<lambda>_80", %4 = "tf.MapDataset"(%3) {device = "", f = @"__inference_Dataset_map_<lambda>_80", output_shapes = [#tf_type.shape<>], output_types = [i32],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils_test.cc
SmallVector<int64_t, 2> output_shape{1, mlir::ShapedType::kDynamic}; EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getShape().size(), output_shape.size()); for (int i = 0; i < output_shape.size(); i++) { EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getDimSize(i), output_shape[i]); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/tests/end2end.mlir
%drop_remainder: i1 {tfr.name="drop_remainder"}, %f: !tfr.attr {tfr.name="func"}, %output_types: !tfr.attr {tfr.name="output_types"}, %output_shapes: !tfr.attr {tfr.name="output_shapes"}, %preserve_cardinality: i1 {tfr.name="preserve_cardinality", tfr.default=false}) -> !tfr.tensor { %batch = "tfr.constant_tensor"(%batch_size) : (i64) -> tensor<i64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 13.4K bytes - Viewed (0)