*/

package org.gradle.internal.snapshot.impl;

import org.gradle.internal.snapshot.ValueSnapshot;
import org.gradle.internal.snapshot.ValueSnapshotter;

/**
 * A snapshot of an immutable scalar value. Should only be used for immutable JVM provided or core Gradle types.
 *
 * @param <T> the type of the value
 */
abstract class AbstractScalarValueSnapshot<T> implements ValueSnapshot {
    private final T value;

//
// Computation of the reduction axis for the Sum op depends on whether the
// input is a scalar or not. Restrict pattern to ranked inputs so that input to
// the Sum op is also ranked.

// TODO(hinsu): Support scalar inputs by introducing reshape to 1D.
def NonScalarType : Type<Neg<HasAnyRankOfPred<[0]>>, "Non scalar type">;

def LowerSoftmaxCrossEntropyWithLogitsOp : Pattern<

				AllowedPodNumber: 80,
				ScalarResources:  map[v1.ResourceName]int64{"scalar.test/scalar1": 1, "hugepages-test": 2},
			},
			expected: &Resource{
				MilliCPU:         4,
				Memory:           2000,
				EphemeralStorage: 5000,
				AllowedPodNumber: 80,
				ScalarResources:  map[v1.ResourceName]int64{"scalar.test/scalar1": 1, "hugepages-test": 2},
			},
		},
	}

	for i, test := range tests {

      const Tensor& max_tensor = context->input(3 * idx + 1);
      const Tensor& histogram_tensor = context->input(3 * idx + 2);

      const float min_value = min_tensor.scalar<float>()();
      const float max_value = max_tensor.scalar<float>()();
      auto histogram_flat = histogram_tensor.flat<int64_t>();
      absl::Span<const int64_t> histogram_data =
          absl::MakeSpan(histogram_flat.data(), histogram_flat.size());

    ConvertToTensorShapeProto(tensor_type.getShape(), &tensor_shape_proto);
    return PartialTensorShape(tensor_shape_proto);
  }

  // If type is not a RankedTensor or UnrankedTensor, it must be a scalar.
  // Empty TensorShape indicates a scalar.
  return TensorShape();
}

mlir::TF::ShapeAttr ConvertTypeToTensorShapeAttr(const mlir::Type& type) {
  if (mlir::isa<mlir::UnrankedTensorType>(type)) {

	//
	// 1) `atomic`: the list is treated as a single entity, like a scalar.
	//      Atomic lists will be entirely replaced when updated. This extension
	//      may be used on any type of list (struct, scalar, ...).
	// 2) `set`:
	//      Sets are lists that must not have multiple items with the same value. Each
	//      value must be a scalar, an object with x-kubernetes-map-type `atomic` or an

	//
	// 1) `atomic`: the list is treated as a single entity, like a scalar.
	//      Atomic lists will be entirely replaced when updated. This extension
	//      may be used on any type of list (struct, scalar, ...).
	// 2) `set`:
	//      Sets are lists that must not have multiple items with the same value. Each
	//      value must be a scalar, an object with x-kubernetes-map-type `atomic` or an

// Creates an 1D array const with float values.
class Create1DConst<string values> : NativeCodeCall<
  "Create1DConstValue<float>($_builder, $_loc, "# values #")">;

// Creates a scalar const with float value.
class CreateScalarConst<string value> : NativeCodeCall<
  "CreateScalarConstValue<float>($_builder, $_loc, "# value #")">;

// Creates an 1D array const with integer values.

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// This is an optimization check. We want to make sure that we compare
// string lengths, and other scalar fields, before checking string
// contents.  There's no way to verify this in the language, and
// codegen tests in test/codegen can't really detect ordering
// optimizations like this. Instead, we generate invalid strings with

@needs_pydanticv1
def test_union_scalar_list():
    # For coverage
    # TODO: there might not be a current valid code path that uses this, it would
    # potentially enable query parameters defined as both a scalar and a list
    # but that would require more refactors, also not sure it's really useful
    from fastapi._compat import is_pv1_scalar_field

    field_info = FieldInfo()
    field = ModelField(
        name="foo",