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tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/reduce.cc
return success(); } // Pattern matches the following reduction function for ArgMax/ArgMin: // %0 = compare{GT}(%lhs_value, %rhs_value) // %1 = compare{NE}(%lhs_value, %lhs_value) // %2 = or(%0, %1) // %3 = select(%2, %lhs_value, %rhs_value) // %4 = compare{EQ}(%lhs_value, %rhs_value) // %5 = compare{LT}(%lhs_index, %rhs_index) // %6 = and(%4, %5) // %7 = or(%2, %6) // %8 = select(%7, %lhs_index, %rhs_index)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 20:53:17 UTC 2024 - 8K bytes - Viewed (0) -
docs/de/docs/tutorial/dependencies/sub-dependencies.md
async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]): return {"fresh_value": fresh_value} ``` === "Python 3.8+ nicht annotiert" !!! tip "Tipp" Bevorzugen Sie die `Annotated`-Version, falls möglich. ```Python hl_lines="1" async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat Mar 30 18:09:48 UTC 2024 - 6.3K bytes - Viewed (0) -
docs/en/docs/tutorial/dependencies/sub-dependencies.md
```Python hl_lines="1" async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]): return {"fresh_value": fresh_value} ``` === "Python 3.8+ non-Annotated" !!! tip Prefer to use the `Annotated` version if possible. ```Python hl_lines="1" async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat May 18 23:43:13 UTC 2024 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
dot_dimension_nums.getRhsContractingDimensions(); const auto lhs_contracting_dims = dot_dimension_nums.getLhsContractingDimensions(); const Value rhs_value = op.getRhs(); const Value lhs_value = op.getLhs(); Operation* rhs_op = rhs_value.getDefiningOp(); auto filter_constant_op = dyn_cast_or_null<stablehlo::ConstantOp>(rhs_op); // Set to `nullptr` because this attribute only matters when the input is
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
docs/ja/docs/tutorial/dependencies/sub-dependencies.md
高度なシナリオでは、「キャッシュされた」値を使うのではなく、同じリクエストの各ステップ(おそらく複数回)で依存関係を呼び出す必要があることがわかっている場合、`Depens`を使用する際に、`use_cache=False`というパラメータを設定することができます。 ```Python hl_lines="1" async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)): return {"fresh_value": fresh_value} ``` ## まとめ ここで使われている派手な言葉は別にして、**依存性注入** システムは非常にシンプルです。 *path operation関数*と同じように見えるただの関数です。 しかし、それでも非常に強力で、任意の深くネストされた依存関係「グラフ」(ツリー)を宣言することができます。
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Mon Jan 15 16:43:41 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics_collector_test.cc
EXPECT_TRUE(statistics.has_value()); EXPECT_EQ(statistics.value().min_max_statistics().global_min(), -5.0f); EXPECT_EQ(statistics.value().min_max_statistics().global_max(), 10.0f); collector.ClearData(); statistics = collector.GetStatistics(); EXPECT_FALSE(statistics.has_value()); collector.Collect( /*min=*/1.0f, /*max=*/10.f, /*histogram=*/{});
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 16 04:33:52 UTC 2024 - 12.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/rewrite_util.h
DenseElementsAttr GetScalarOfType(Type ty, T raw_value) { RankedTensorType scalar_ty = RankedTensorType::get({}, ty); if (auto float_ty = mlir::dyn_cast<FloatType>(ty)) { FloatAttr attr = FloatAttr::get(float_ty, raw_value); return DenseElementsAttr::get(scalar_ty, attr); } else if (auto int_ty = mlir::dyn_cast<IntegerType>(ty)) { IntegerAttr attr = IntegerAttr::get(int_ty, raw_value); return DenseElementsAttr::get(scalar_ty, attr);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/ir/tfrt_fallback_common.h
auto op_func_attr_array = op.getOpFuncAttrs().getValue(); for (auto op_attr : op_func_attr_array) { auto key_value = mlir::dyn_cast<mlir::ArrayAttr>(op_attr); if (!key_value || key_value.getValue().size() != 2 || !mlir::isa<mlir::StringAttr>(key_value.getValue()[0]) || !mlir::isa<mlir::StringAttr>(key_value.getValue()[1])) return op.emitOpError() << "each op_func_attr should be a key-value "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.5K bytes - Viewed (0) -
plugin/pkg/admission/podtolerationrestriction/admission_test.go
namespaceTolerations: []api.Toleration{}, podTolerations: []api.Toleration{{Key: "testKey", Operator: "Equal", Value: "testValue", Effect: "NoSchedule", TolerationSeconds: nil}}, mergedTolerations: []api.Toleration{{Key: "testKey", Operator: "Equal", Value: "testValue", Effect: "NoSchedule", TolerationSeconds: nil}},
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Wed Mar 06 00:00:21 UTC 2024 - 16K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/ir/tfrt_fallback_common.cc
assert(op_attrs); op_attrs->clear(); mlir::Builder builder(context); for (auto iter : op_attr_array) { auto key_value = mlir::cast<mlir::ArrayAttr>(iter).getValue(); llvm::StringRef key = mlir::cast<mlir::StringAttr>(key_value[0]).getValue(); mlir::Attribute value = key_value[1]; op_attrs->push_back({key, value}); } } mlir::ParseResult ParseExecuteOpCommon(mlir::OpAsmParser &parser,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.2K bytes - Viewed (0)