petastorm/codecs.py [136:151]:
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    def encode(self, unischema_field, value):
        expected_dtype = unischema_field.numpy_dtype
        if isinstance(value, np.ndarray):
            if expected_dtype != value.dtype.type:
                raise ValueError('Unexpected type of {} feature. '
                                 'Expected {}. Got {}'.format(unischema_field.name, expected_dtype, value.dtype))

            expected_shape = unischema_field.shape
            if not _is_compliant_shape(value.shape, expected_shape):
                raise ValueError('Unexpected dimensions of {} feature. '
                                 'Expected {}. Got {}'.format(unischema_field.name, expected_shape, value.shape))
        else:
            raise ValueError('Unexpected type of {} feature. '
                             'Expected ndarray of {}. Got {}'.format(unischema_field.name, expected_dtype, type(value)))

        memfile = BytesIO()
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petastorm/codecs.py [177:192]:
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    def encode(self, unischema_field, value):
        expected_dtype = unischema_field.numpy_dtype
        if isinstance(value, np.ndarray):
            if expected_dtype != value.dtype.type:
                raise ValueError('Unexpected type of {} feature. '
                                 'Expected {}. Got {}'.format(unischema_field.name, expected_dtype, value.dtype))

            expected_shape = unischema_field.shape
            if not _is_compliant_shape(value.shape, expected_shape):
                raise ValueError('Unexpected dimensions of {} feature. '
                                 'Expected {}. Got {}'.format(unischema_field.name, expected_shape, value.shape))
        else:
            raise ValueError('Unexpected type of {} feature. '
                             'Expected ndarray of {}. Got {}'.format(unischema_field.name, expected_dtype, type(value)))

        memfile = BytesIO()
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