def _sparse_dense_truediv(sp_indices, sp_values, sp_shape, y, name=None):
    "Internal helper function for 'sp_t / dense_t'."
    with ops.name_scope(name, 'truediv', [sp_indices, sp_values, sp_shape, y]) as name:
        sp_values = ops.convert_to_tensor(sp_values, name='sp_values')
        y = ops.convert_to_tensor(y, name='y')
        x_dtype = sp_values.dtype.base_dtype
        y_dtype = y.dtype.base_dtype
        if (x_dtype != y_dtype):
            raise TypeError(('x and y must have the same dtype, got %r != %r' % (x_dtype, y_dtype)))
        try:
            dtype = _TRUEDIV_TABLE[x_dtype]
        except KeyError:
            raise TypeError(('Invalid dtype %r in __truediv__' % x_dtype))
        if (dtype is not None):
            sp_values = cast(sp_values, dtype)
            y = cast(y, dtype)
        return gen_sparse_ops.sparse_dense_cwise_div(sp_indices, sp_values, sp_shape, y, name=name)
Internal helper function for 'sp_t / dense_t'.
def _sparse_dense_truediv(sp_indices, sp_values, sp_shape, y, name=None):
    
    with ops.name_scope(name, 'truediv', [sp_indices, sp_values, sp_shape, y]) as name:
        sp_values = ops.convert_to_tensor(sp_values, name='sp_values')
        y = ops.convert_to_tensor(y, name='y')
        x_dtype = sp_values.dtype.base_dtype
        y_dtype = y.dtype.base_dtype
        if (x_dtype != y_dtype):
            raise TypeError(('x and y must have the same dtype, got %r != %r' % (x_dtype, y_dtype)))
        try:
            dtype = _TRUEDIV_TABLE[x_dtype]
        except KeyError:
            raise TypeError(('Invalid dtype %r in __truediv__' % x_dtype))
        if (dtype is not None):
            sp_values = cast(sp_values, dtype)
            y = cast(y, dtype)
        return gen_sparse_ops.sparse_dense_cwise_div(sp_indices, sp_values, sp_shape, y, name=name)