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Results 11 - 20 of 51 for isF32 (0.08 sec)
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tensorflow/compiler/mlir/lite/transforms/while_loop_outline.cc
} bool IsCompatibleTypeWithTFLCastOp(Type type) { auto elemType = getElementTypeOrSelf(type); // F16, F32, F64, BF16 types are allowed. if (elemType.isBF16() || elemType.isF16() || elemType.isF32() || elemType.isF64()) return true; // I1, I4, I8, I16, I32, I64 types are allowed. if (elemType.isInteger(1) || elemType.isInteger(4) || elemType.isInteger(8) ||
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/optimize.td
Constraint<CPred<"TFL::IsBroadcastableElementsAttrs($0, $1) && TFL::IsDimensionsDegenerateExceptLastOne($1)">>; def F32ElementsAttr : ElementsAttrBase< CPred<"$_self.cast<ElementsAttr>().getShapedType().getElementType().isF32()">, "float constant tensor">; def DefinedByConv2D : Constraint<CPred<"llvm::isa_and_nonnull<mlir::TF::Conv2DOp>($0.getDefiningOp())">>; // Checks if the value has only one user. def HasOneUse : Constraint<CPred<"$0.hasOneUse()">>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 22 07:31:23 UTC 2023 - 5.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/unfold_large_splat_constant.cc
mlir::dyn_cast<SplatElementsAttr>(const_op.getValue()); if (!splat_elements_attr) { return; } auto element_type = splat_elements_attr.getType().getElementType(); if (!(element_type.isF32() || element_type.isF16() || element_type.isInteger(1) || element_type.isInteger(32) || element_type.isInteger(64))) { return; } if (splat_elements_attr.getNumElements() *
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/dense_to_sparse.cc
std::vector<int> b_size = {}; std::vector<int> b_map = {}; PopulateEncodingParams(block_size, &traversal_order, &format, &b_map, &b_size); if (type.getElementType().isF32()) { tflite::internal::sparsity::FormatConverter<float> format_converter( shape, traversal_order, format, b_size, b_map); std::vector<float> data; data.reserve(type.getNumElements());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/fused_kernel_matcher.cc
<< ")"; }); return false; } // Verify the data type is supported. Type element_ty = getElementTypeOrSelf(conv.getType()); if (!element_ty.isF32() && !element_ty.isF64()) { (void)rewriter.notifyMatchFailure(conv, [&](Diagnostic &diag) { diag << "supported data types for _FusedConv2D are float and double, " << " but got " << element_ty;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/validators.h
// is "DT_FLOAT". inline bool TFTypeIsFloat32Tensor(Value value) { auto tensorType = mlir::dyn_cast<TensorType>(value.getType()); if (!tensorType) return false; return tensorType.getElementType().isF32(); } // Returns true iff the given value is a bf16 tensor. inline bool TFTypeIsBFloat16Tensor(Value value) { auto tensorType = mlir::dyn_cast<TensorType>(value.getType()); if (!tensorType) return false;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/ops/tf_op_quant_spec.cc
} bool IsValueWithQuantizablePrecision(Value val) { auto type = mlir::dyn_cast<ShapedType>(val.getType()); if (!type) return false; // Supported original tensor data types. if (type.getElementType().isF32() || type.getElementType().isBF16()) return true; return false; } std::optional<tensorflow::quantization::QuantizationComponentSpec> GetWeightComponentSpec(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantize.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 23.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform.cc
if (!IsQI32Type(input_dequant.getType())) return failure(); auto output_type = mlir::dyn_cast_or_null<ShapedType>(dequant_op.getOutput().getType()); if (!output_type || !output_type.getElementType().isF32()) return failure(); auto input_type = mlir::dyn_cast<ShapedType>(input_dequant.getType()); // TODO(renjieliu): support UniformQuantizedPerAxisType.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/fold_constant_transpose.cc
if (!const_op) return failure(); // Only support float tensors. auto tensor_type = mlir::dyn_cast_or_null<TensorType>(const_op.getType()); if (!tensor_type || !tensor_type.getElementType().isF32()) { return failure(); } return success( mlir::isa_and_nonnull<DenseFPElementsAttr>(const_op.getValue())); } void rewrite(mlir::stablehlo::TransposeOp op,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.7K bytes - Viewed (0)