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Results 1 - 10 of 191 for output_types (0.14 sec)
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tensorflow/compiler/mlir/tensorflow/tests/name_anonymous_iterators.mlir
// 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> // CHECK: "tf.Iterator" // CHECK-SAME: shared_name = "_iterator2"
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/lite/utils/perception_ops_utils_test.cc
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}; SmallVector<mlir::Type, 1> output_types{output_type}; return createMaxUnpoolingFunc<2, 1>(builder, input_types, output_types); } template <int N>
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/tfrt/tests/tf_to_corert/func_attributes_multiple_callers.mlir
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
// 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 = "__inference_Dataset_flat_map_lambda_19"} : 1
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/lite/utils/lstm_utils_test.cc
auto output_types = fused_lstm_func_.getFunctionType().getResults(); 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/tensorflow/tests/decompose_reduce_dataset.mlir
%1 = "tf.ReduceDataset"(%arg0, %arg1) { Targuments = [], Tstate = [i64], device = "", f = @__reduce_func_0, f._tf_data_function = true, output_shapes = [#tf_type.shape<>], output_types = [i64], use_inter_op_parallelism = true } : (tensor<!tf_type.variant>, tensor<i64>) -> (tensor<i64>) func.return }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 18 17:16:34 UTC 2022 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.h
} // Collect all the quantized outputs and replace them by the results of // the new quantized op. llvm::SmallDenseMap<Value, int> outputs_replaced; SmallVector<Type, 4> output_types; output_types.reserve(candidate_op->getNumResults()); for (const auto& enumerated_result : llvm::enumerate(candidate_op->getResults())) { Value result = enumerated_result.value();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_data_fuse_map_and_batch.mlir
output_shapes = [#tf_type.shape<>], output_types = [i32], preserve_cardinality = false, sloppy = false, use_inter_op_parallelism = true, metadata = ""} : (tensor<*x!tf_type.variant>) -> tensor<!tf_type.variant> %5 = "tf.BatchDatasetV2"(%4, %0, %1) {device = "", output_shapes = [#tf_type.shape<>], output_types = [i32], parallel_copy = false,
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/tensorflow/transforms/host_runtime/tpu_merge_variables_with_execute.cc
// (inclusive) to `end` index region (exclusive) to `output_types` and returns // the number of types added. int AppendTypes(llvm::SmallVectorImpl<Type>* output_types, tf_device::ParallelExecuteOp parallel_execute, int start, int end) { const int size_before = output_types->size(); for (int index = start; index < end; ++index) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 29 17:52:11 UTC 2024 - 27K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/tf-data-pipeline.pbtxt
} } } attr { key: "output_shapes" value { list { shape { } } } } attr { key: "output_types" value { list { type: DT_INT32 } } } attr { key: "preserve_cardinality" value { b: false } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 29 04:41:05 UTC 2021 - 4K bytes - Viewed (0)