- Sort Score
- Result 10 results
- Languages All
Results 111 - 120 of 1,054 for ShapeN (0.09 sec)
-
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/prune_unused_nodes.pbtxt
# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-prune-unused-nodes -tf-input-arrays=input0,input1 -tf-input-data-types=DT_INT32,DT_INT32 -tf-input-shapes=10:10 -tf-output-arrays=Add -o - | FileCheck %s # Verify that an unused Node (here named "Prune") isn't converted when we # request pruning on import. # CHECK-LABEL: func @main # CHECK-NOT: Prune # CHECK-NOT: unused_input node { name: "Prune" op: "Const"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 24 00:20:25 UTC 2020 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
Value value, ArrayRef<int64_t> shape, Type element_type, Location loc, PatternRewriter& rewriter) { int64_t shape_rank = shape.size(); auto shape_spec_type = RankedTensorType::get({shape_rank}, rewriter.getIntegerType(64)); Type resultType = RankedTensorType::get(shape, element_type); auto constant_attr = DenseElementsAttr::get(shape_spec_type, shape); auto shape_tensor =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
tensor_spec.TensorSpec( shape=shape, dtype=dtypes.float32, name='input_tensor' ) ), ) return model # Prepares sample einsum input data shapes. # This function returns: # 1. Shape for input 1 # 2. Shape for input 2 # 3. Shape for bias # 4. Signature for input 1 (Could contain None dimension)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/extract_outside_compilation.cc
} llvm::SmallVector<int64_t, 4> shape; shape.push_back(split_size); for (int i = 1; i < in_shape.size(); ++i) { shape.push_back(in_shape[i]); } shard_type = RankedTensorType::Builder(ranked_type).setShape(shape); return mlir::success(); } // Output `sharding`, which is the sharding of `val`. `context_op` is used for // error reporting, in case of errors.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 68.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.h
bool lower_to_xla_hlo = true, bool allow_partial_conversion = false); // Helper struct representing argument tensor or resource handle shapes. struct TensorOrResourceShape { TensorShape shape; bool is_resource = false; }; // Refine MLIR types based on new shape information. ABSL_DEPRECATED("Not meant to be used directly and should be a util.") Status RefineShapes(llvm::ArrayRef<TensorOrResourceShape> arg_shapes,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 10.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_tensor_helper.h
namespace TF { // Returns the RankedTensorType for the given operand. TensorFlow constant ops // may have non-static shape because the shape is not propagated during constant // folding. If the defining op for the given operand is a constant op, this // routine uses the constant op's attribute to get the actual shape. RankedTensorType GetRankedTensorTypeForOperand(Value operand);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tpu_annotate_dynamic_shape_inputs.cc
// Mark the dim as dynamic dim. shape[0] = ShapedType::kDynamic; auto extensions = mhlo::TypeExtensionsAttr::get(func->getContext(), bounds); auto resultType = RankedTensorType::get(shape, inputType.getElementType(), extensions); arg.setType(resultType); } llvm::SmallVector<Type, 8> arg_types;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/functional-while-ops.pbtxt
# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-input-arrays=iter,val -tf-input-data-types=DT_INT32,DT_FLOAT -tf-input-shapes=':' -tf-output-arrays=StatefulWhile:1,StatelessWhile:1,WhileWithOutputShapes:1 -o - -mlir-print-debuginfo -mlir-print-local-scope | FileCheck %s # Verify that TensorFlow While and StatelessWhile ops are mapped to the # composite While op in MLIR with is_stateless attribute set accordingly to
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 15 19:42:47 UTC 2021 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/conv_2d_nchw.pbtxt
# RUN: tf_tfl_translate -tf-input-arrays=input -tf-input-shapes=1,2,8,2 -tf-input-data-types=DT_FLOAT -tf-output-arrays=output_0 -print-function-result-mapping %s -o - 2>&1 | FileCheck %s node { name: "input" op: "Placeholder" attr { key: "dtype" value { type: DT_FLOAT } } attr { key: "shape" value { shape { dim { size: 1 } dim { size: 2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 03 03:26:13 UTC 2021 - 3.7K bytes - Viewed (0)