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Results 1 - 10 of 14 for lhs0 (0.11 sec)
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tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.cc
// Hoist coefficient-wise binary operation out of the Concat op: // // %0 = tf.Mul(%lhs_0, %rhs_0) // %1 = tf.Mul(%lhs_1, %rhs_1) // ... // %n = tf.Mul(%lhs_n, %rhs_n) // %m = tf.ConcatV2(%0, %1, ..., %n, %axis) // // Rewrite it to: // // %0 = tf.ConcatV2(%lhs0, %lhs1, ..., %lhs_n, %lhs_concat_axis) // %1 = tf.ConcatV2(%rhs0, %rhs1, ..., %rhs_n, %rhs_concat_axis) // %2 = tf.Mul(%0, %1) //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 146.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.cc
// dimensions must be equal to be compatible) and identical element types. bool VerifyCompatibleShapesSameElementType(TypeRange lhs, TypeRange rhs) { if (lhs.size() != rhs.size() || lhs.size() != 1) return false; if (failed(mlir::verifyCompatibleShape(lhs[0], rhs[0]))) return false; auto lhsShaped = lhs[0].cast<ShapedType>(); auto rhsShaped = rhs[0].cast<ShapedType>(); return lhsShaped.getElementType() == rhsShaped.getElementType();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 169.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
OpBuilder<(ins "Value":$lhs, "Value":$rhs, "StringAttr":$fusedActivationFunction), [{ buildFusedBroadcastableBinOp( &$_builder, $_state, lhs, rhs, fusedActivationFunction); }]>; def TFL_ComparisonBinaryBuilder : OpBuilder<(ins "Value":$lhs, "Value":$rhs), [{ buildComparisonBinOp(&$_builder, $_state, lhs, rhs); }]>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
// // In case of inconsistencies (rank disagreement for example), it returns `lhs`. Type TypeMeet(Type lhs, Type rhs) { DCOMMENT("RefineTypeWith : " << lhs << " : " << rhs); if (lhs == rhs) return lhs; auto rhs_shape_type = mlir::dyn_cast<ShapedType>(rhs); if (!rhs_shape_type) return lhs; auto lhs_shape_type = mlir::cast<ShapedType>(lhs); if (lhs_shape_type.hasRank() && rhs_shape_type.hasRank() &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
// expected-error @below {{'tf.XlaConvV2' op Expected the size of kernel_input_features (value 16) in rhs times feature_group_count (value 2) in lhs should equal the size of the z dimension (value 16) in lhs.}}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
fc_op.getAsymmetricQuantizeInputsAttr()); rewriter.replaceOp(add_op, fc.getOutput()); return success(); } }; // Replace .. // FC(Add(lhs, rhs), filter, bias) // .. with .. // FC(lhs, filter, FC(rhs, filter, bias)) // .. if rhs, filter, and bias are all constants. // The second FC will be constant folded to a single vector.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
int input_channels, ConversionPatternRewriter& rewriter) const { mhlo::ConvDimensionNumbersAttr dnums = conv_op.getDimensionNumbers(); // Transposes lhs and rhs if their formats are not NHWC. Value lhs = InsertTranspose( conv_op.getLhs(), dnums.getInputBatchDimension(), dnums.getInputFeatureDimension(), dnums.getInputSpatialDimensions(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
: public OpRewritePattern<stablehlo::DotGeneralOp> { public: using OpRewritePattern<stablehlo::DotGeneralOp>::OpRewritePattern; LogicalResult match(stablehlo::DotGeneralOp op) const override { // Lhs and result should not be quantized and rhs should be quantized. return success(!IsQuantizedTensorType(op->getOperand(0).getType()) && IsQuantizedTensorType(op->getOperand(1).getType()) &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/import_model.cc
llvm::sort(inputs, [](const auto& lhs, const auto& rhs) { return tensorflow::Fingerprint64(lhs.first) < tensorflow::Fingerprint64(rhs.first); }); std::vector<std::pair<std::string, TensorInfo>> outputs( signature_def.outputs().begin(), signature_def.outputs().end()); llvm::sort(outputs, [](const auto& lhs, const auto& rhs) { return tensorflow::Fingerprint64(lhs.first) <
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 183.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc
XlaBroadcastHelperOpAdaptor op(operands.getValues(), attributes); Value lhs = op.getLhs(); Value rhs = op.getRhs(); auto set_unranked_results = [&]() { inferredReturnShapes.emplace_back(getElementTypeOrSelf(lhs)); inferredReturnShapes.emplace_back(getElementTypeOrSelf(rhs)); return success(); }; RankedTensorType lhs_ty = lhs.getType().dyn_cast<RankedTensorType>();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0)