package main

import "runtime"

func assert[_ any]() {
	panic(0)
}

func Assert[To any]() func() {
	return assert[To]
}

type asserter[_ any] struct{}

func (asserter[_]) assert() {
	panic(0)
}

func AssertMV[To any]() func() {
	return asserter[To]{}.assert
}

func AssertME[To any]() func(asserter[To]) {
	return asserter[To].assert
}

var me = AssertME[string]()

type DynamicType struct {
	miniExpr

	// RType is an expression that yields a *runtime._type value
	// representing the asserted type.
	//
	// BUG(mdempsky): If ITab is non-nil, RType may be nil.
	RType Node

	// ITab is an expression that yields a *runtime.itab value
	// representing the asserted type within the assertee expression's
	// original interface type.
	//
	// ITab is only used for assertions (including type switches) from

    }]
    combinations = testing.parameter_combinations(test_parameters)

    self.assertLen(combinations, 4)
    self.assertIn({'shapes': [3, 3], 'has_bias': True}, combinations)
    self.assertIn({'shapes': [3, 3], 'has_bias': False}, combinations)
    self.assertIn({'shapes': [3, None], 'has_bias': True}, combinations)
    self.assertIn({'shapes': [3, None], 'has_bias': False}, combinations)


class FileSizeTestCase(test.TestCase):

		t.Fatalf("found diff: %v\nGot: %v\nWant: %v", cmp.Diff(a, expected, opts(expected)...), a, expected)
	}
}

// Error asserts the provided err is non-nil
func Error(t test.Failer, err error) {
	t.Helper()
	if err == nil {
		t.Fatal("expected error but got nil")
	}
}

// NoError asserts the provided err is nil
func NoError(t test.Failer, err error) {
	t.Helper()
	if err != nil {

    sample = {'input_tensor': input_tensor_value}

    feed_dict = repr_dataset.create_feed_dict_from_input_data(
        sample, signature_def
    )

    self.assertLen(feed_dict, 1)
    self.assertIn('input:0', feed_dict)
    self.assertAllEqual(feed_dict['input:0'], input_tensor_value)

  @test_util.deprecated_graph_mode_only
  def test_create_feed_dict_from_input_data_core_tensors(self):

  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(status.get()));
  ASSERT_EQ(device_name, nullptr);
  ASSERT_EQ("Invalid handle", string(TF_Message(status.get())));

  TF_SetStatus(status.get(), TF_OK, "");

  int num_dims = TFE_TensorHandleNumDims(h, status.get());
  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(status.get()));
  ASSERT_EQ(num_dims, -1);
  ASSERT_EQ("Invalid handle", string(TF_Message(status.get())));

func.func @preserve_assert(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<1xi1> {
  %0 = "tf.LessEqual"(%arg0, %arg1) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi1>
  "tf.Assert"(%0, %arg1) {summarize = 3} : (tensor<1xi1>, tensor<1xi32>) -> ()
  func.return %0 : tensor<1xi1>
  // CHECK-LABEL: preserve_assert
  // CHECK: tfl.less_equal
  // CHECK: Assert
  // CHECK: return

            val strAssignment = elements.find { it.lhs.property.name == "str" }
            assertIs<AssignmentTraceElement.RecordedAssignment>(strAssignment)
            val value = resolvedAssignments[strAssignment.lhs]
            assertIs<AssignmentResolver.AssignmentResolutionResult.Assigned>(value)
            val valueOrigin = value.objectOrigin
            assertIs<ObjectOrigin.ConstantOrigin>(valueOrigin)

      TFE_NewOp(context.get(), function_name, status.get()), TFE_DeleteOp);
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  TFE_OpSetDevice(op.get(), device_name, status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  TFE_OpAddInput(op.get(), parallel_value.get(), status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  ASSERT_TRUE(succeeded(res));
  ASSERT_EQ(2147483647, op.getLhsQuantizationMaxValAttr().getInt());
  ASSERT_EQ(-2147483648, op.getLhsQuantizationMinValAttr().getInt());
  ASSERT_EQ(2147483647, op.getRhsQuantizationMaxValAttr().getInt());
  ASSERT_EQ(-2147483648, op.getRhsQuantizationMinValAttr().getInt());
  ASSERT_EQ(2147483647, op.getOutputQuantizationMaxValAttr().getInt());