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Results 11 - 20 of 24 for mat_mul (0.25 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir
func.func private @composite_matmul_with_bias_fn_1(%arg0: tensor<1x4xf32>, %arg1: tensor<4x3xf32>, %arg2: tensor<3xf32>) -> tensor<1x3xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) <{grad_a = false, grad_b = false, transpose_a = false, transpose_b = false}> {attr_map = "0:transpose_a,1:transpose_b", device = ""} : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 32.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_composite_functions_tf.cc
return func_.emitWarning() << "Invalid number of arguments in the embedding " "matmul composite function"; } if (func_.getFunctionType().getNumResults() != 1) { return func_.emitWarning() << "Invalid number of results in the " "embedding matmul composite function"; } return success(); } private: func::FuncOp func_; };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
#include "xla/xla_data.pb.h" namespace mlir::quant { namespace { constexpr StringRef kTfQuantCreatedEinsum = "__tf_quant_created_einsum"; // Replaces mixed-type Conv and Matmul cast hacks with TF XLA ops. // TODO(b/228403741): Support conversion for dynamic-shaped TF ops. class ReplaceCastHacksWithTFXLAOpsPass : public PassWrapper<ReplaceCastHacksWithTFXLAOpsPass,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 47.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
loc, value, Create1DConstValue(builder, loc, new_shape)); } return ConstantFoldOpIfPossible(value.getDefiningOp()).front(); } // Matches convolution op with "NHWC" data format or matmul op with false adj_y. // The list of supported ops in this function is: // - Conv2DOp // - Conv3DOp // - DepthwiseConv2dNativeOp // - MatMulOp // - BatchMatMulV2Op
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/lite/transforms/passes.td
"bool", "false", "Disable folding mul and fully connected ops during optimization pass.">, ]; } def OptimizeBatchMatmulPass : Pass<"tfl-optimize-batch-matmul", "mlir::func::FuncOp"> { let summary = "Optimize FC with BatchMatmul within the TensorFlow Lite dialect"; let constructor = "CreateOptimizeBatchMatmulPass()"; let dependentDialects = ["TFL::TensorFlowLiteDialect"]; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 22.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/passes.h
std::unique_ptr<OperationPass<mlir::func::FuncOp>> CreateOptimizePass(); // Creates an instance of the ReplaceCastHacksWithTFXLAOpsPass, which will // replace mixed-type convolution and matmul cast hacks by XLA Conv2DOp and // MatmulOp. std::unique_ptr<OperationPass<func::FuncOp>> CreateReplaceCastHacksWithTFXLAOpsPass(); // Creates a pass that moves & merges initializer function's ops into the @main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 12.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
DECL_CONVERT_OP(Assert); DECL_CONVERT_OP(ConcatV2); DECL_CONVERT_OP(BatchMatMul); DECL_CONVERT_OP(BatchMatMulV2); DECL_CONVERT_OP(BatchMatMulV3); DECL_CONVERT_OP(MatMul); DECL_CONVERT_OP(MatrixDiagV2); DECL_CONVERT_OP(MatrixDiagV3); DECL_CONVERT_OP(Pack); DECL_CONVERT_OP(Split); DECL_CONVERT_OP(SplitV); DECL_CONVERT_OP(Unpack); DECL_CONVERT_OP(Conv3D);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/control_flow.mlir
%x = "tf.TensorArrayReadV3"(%handle_0, %index, %flow_0) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<2x!tf_type.resource<tensor<?x100xf32>>>, tensor<i32>, tensor<f32>) -> tensor<?x100xf32> %y = "tf.MatMul"(%x, %cst) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<?x100xf32>, tensor<100x512xf32>) -> (tensor<?x512xf32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 00:40:32 UTC 2024 - 17.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call.cc
// identifier is the order of that attribute in `attributes`. This map // is then used to set attributes in the quantized functions in the // QuantizeCompositeFunctionsPass. // For example, for tf.MatMul with `attributes` = {{"transpose_a", false}, // {"transpose_b", false}}, the generated attr_map is // "0:transpose_a,1:transpose_b", where 0 and 1 are the respective attribute // identifiers.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 21.8K bytes - Viewed (0)