{
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

import (
	"testing"
)

func TestEvalSQLLike(t *testing.T) {
	dropCases := []struct {
		input, resultExpected string
		matchExpected         bool
	}{
		{"", "", false},
		{"a", "", true},
		{"ab", "b", true},
		{"தமிழ்", "மிழ்", true},
	}

	for i, tc := range dropCases {
		res, ok := dropRune(tc.input)
		if res != tc.resultExpected || ok != tc.matchExpected {
			t.Errorf("DropRune Case %d failed", i)
		}

    validations:
      required: true
  - type: input
    id: gradle-version
    attributes:
      label: Gradle version
      description: What version of Gradle are you running?
    validations:
      required: true
  - type: input
    id: build-scan-url
    attributes:
      label: Build scan URL (optional)
      description: |

  }
};

// An abstract operation describes an operation by its type, name, and
// attributes. It can be "executed" by the context with some input tensors.
// It is allowed to reusing the same abstract operation for multiple execution
// on a given context, with the same or different input tensors.
class TracingOperation : public AbstractOperation {
 protected:
  explicit TracingOperation(AbstractOperationKind kind)

        return lenToRead;
      }
    }
  }

  /**
   * @param input the size of the input source
   * @param offset the first argument to {@link ByteSource#slice}
   * @param length the second argument to {@link ByteSource#slice}
   * @param expectRead the number of bytes we expect to read
   */
  private static void assertCorrectSlice(int input, int offset, long length, int expectRead)
      throws IOException {

            final VaErrorHook hook) {
        return getEntity(form).map(entity -> {
            final String newInput = form.input;
            validateProtwordsString(action, newInput, "input", hook);
            entity.setNewInput(newInput);
            return entity;
        });
    }

                }

                final String inputStrings = line;
                final String input = unescape(inputStrings);

                if (input.length() > 0) {
                    id++;
                    final ProtwordsItem item = new ProtwordsItem(id, input);
                    if (updater != null) {
                        final ProtwordsItem newItem = updater.write(item);

                }

                final String inputStrings = line;
                final String input = unescape(inputStrings);

                if (input.length() > 0) {
                    id++;
                    final StopwordsItem item = new StopwordsItem(id, input);
                    if (updater != null) {
                        final StopwordsItem newItem = updater.write(item);

        }

        for (final Pattern pattern : includedDocPathPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.TRUE;
            }
        }

        for (final Pattern pattern : excludedDocPathPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.FALSE;
            }
        }

        return Constants.TRUE;

    }

}

void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s) {
  for (int i = 0; i < num_inputs; i++) {
    tsl::Set_TF_Status_from_Status(s, unwrap(op)->AddInput(unwrap(inputs[i])));
    if (TF_GetCode(s) != TF_OK) {
      return;
    }
  }
  int num_outputs = unwrap(o)->expected_num_outputs;