Payne
4 years ago
1 changed files with 57 additions and 47 deletions
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+ 57
- 47
mindspore/ops/composite/multitype_ops/_constexpr_utils.py
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| @@ -147,13 +147,15 @@ def judge_index_type(index_type, target_type): | |||
| @constexpr | |||
| def check_type_valid(dtype, target_type, op_name): | |||
| if dtype != target_type and (isinstance(target_type, (list, tuple)) and dtype not in target_type): | |||
| raise TypeError(f"The '{op_name}' doesn't supoort {dtype}' and expecte to receive {target_type}.") | |||
| raise TypeError( | |||
| f"The '{op_name}' doesn't supoort {dtype}' and expecte to receive {target_type}.") | |||
| @constexpr | |||
| def check_index_type_valid(dtype, target_type, op_name): | |||
| if dtype != target_type and (isinstance(target_type, (list, tuple)) and dtype not in target_type): | |||
| raise IndexError(f"The '{op_name}' doesn't supoort {dtype}' and expecte to receive {target_type}.") | |||
| raise IndexError( | |||
| f"The '{op_name}' doesn't supoort {dtype}' and expecte to receive {target_type}.") | |||
| @constexpr | |||
| @@ -189,7 +191,8 @@ def get_pos_of_indexes_types(indexes_types, op_name): | |||
| raise IndexError(f"For '{op_name}', the index elements only support " | |||
| f"'Tensor', 'int32', 'int64', 'Slice', 'Ellipsis', but got {index_type}.") | |||
| if len(ellipsis_positions) > 1: | |||
| raise IndexError(f"For '{op_name}, an index can only have a single ellipsis('...')") | |||
| raise IndexError( | |||
| f"For '{op_name}, an index can only have a single ellipsis('...')") | |||
| return slice_positions, ellipsis_positions, none_positions, int_positions, bool_positions, \ | |||
| tensor_positions, sequence_positions | |||
| @@ -260,7 +263,7 @@ def ellipsis2slice(input_, shape): | |||
| return tuple(result) | |||
| @ constexpr | |||
| @constexpr | |||
| def slice2indices(input_slices, shape): | |||
| """ | |||
| Converts slice to indices. | |||
| @@ -285,7 +288,7 @@ def slice2indices(input_slices, shape): | |||
| return ravel | |||
| @ constexpr | |||
| @constexpr | |||
| def check_indices(indices_size, index): | |||
| """Checks indices whether is empty.""" | |||
| if indices_size < 1: | |||
| @@ -294,7 +297,7 @@ def check_indices(indices_size, index): | |||
| return indices_size | |||
| @ constexpr | |||
| @constexpr | |||
| def check_indices_value_size(indices_size, value_size): | |||
| """Checks if the sizes are already matched.""" | |||
| if value_size < 1: | |||
| @@ -307,7 +310,7 @@ def check_indices_value_size(indices_size, value_size): | |||
| return value_size | |||
| @ constexpr | |||
| @constexpr | |||
| def integer_to_indices(index, shape): | |||
| """Converts int or tuple[int] to indices.""" | |||
| size = reduce(lambda x, y: x * y, shape) | |||
| @@ -317,7 +320,7 @@ def integer_to_indices(index, shape): | |||
| return Tensor(value, dtype=mstype.int32) | |||
| @ constexpr | |||
| @constexpr | |||
| def tuple_element_is_int(indexs): | |||
| """Judges tuple element type.""" | |||
| if not indexs: | |||
| @@ -330,18 +333,19 @@ def tuple_element_is_int(indexs): | |||
| return False | |||
| @ constexpr | |||
| @constexpr | |||
| def tuple_index_int_cnt(types, op_name): | |||
| """count the int type of types which contains the tuple elements' type.""" | |||
| int_cnt = sum(isinstance(ele, mstype.Int) for ele in types) | |||
| return ALL_INT if int_cnt == len(types) else NO_INT if int_cnt == 0 else CONTAIN_INT | |||
| @ constexpr | |||
| @constexpr | |||
| def tuple_index_type_cnt(types, op_name): | |||
| """count the tensor type of types which contains the tuple elements' type.""" | |||
| tensor_cnt = sum(isinstance(ele, mstype.tensor_type) for ele in types) | |||
| basic_cnt = sum(isinstance(ele, (mstype.Int, mstype.Ellipsis_, mstype.Slice)) for ele in types) | |||
| basic_cnt = sum(isinstance( | |||
| ele, (mstype.Int, mstype.Ellipsis_, mstype.Slice)) for ele in types) | |||
| if tensor_cnt == len(types): | |||
| return ALL_TENSOR | |||
| if basic_cnt == len(types): | |||
| @@ -349,7 +353,7 @@ def tuple_index_type_cnt(types, op_name): | |||
| return MIXED | |||
| @ constexpr | |||
| @constexpr | |||
| def check_value_elements(data_dtype, types): | |||
| """Judges the type of all elements of the tuple.""" | |||
| tensors_number = 0 | |||
| @@ -377,10 +381,10 @@ def check_value_elements(data_dtype, types): | |||
| # TODO to del | |||
| @ constexpr | |||
| @constexpr | |||
| def get_index_tensor_dtype(dtype): | |||
| """Check a tuple of tensor data type.""" | |||
| if dtype == mstype.int32: | |||
| if dtype in mstype.int_type: | |||
| return INT_ | |||
| if dtype == mstype.bool_: | |||
| return BOOL_ | |||
| @@ -389,7 +393,7 @@ def get_index_tensor_dtype(dtype): | |||
| # TODO to del | |||
| @ constexpr | |||
| @constexpr | |||
| def check_index_tensors_dtype(indexes_types, op_name): | |||
| """Check a tuple of tensor data type.""" | |||
| for index_type in indexes_types: | |||
| @@ -400,7 +404,7 @@ def check_index_tensors_dtype(indexes_types, op_name): | |||
| # TODO to del | |||
| @ constexpr | |||
| @constexpr | |||
| def check_index_tensor_dtype(index_type, op_name): | |||
| """Check a tensor data type.""" | |||
| if index_type in (mstype.int32, mstype.int64): | |||
| @@ -410,7 +414,7 @@ def check_index_tensor_dtype(index_type, op_name): | |||
| # TODO to del | |||
| @ constexpr | |||
| @constexpr | |||
| def check_tensors_dtype_same(data_dtype, value_dtype, op_name): | |||
| """Check tensors data type same.""" | |||
| if value_dtype == data_dtype: | |||
| @@ -419,7 +423,7 @@ def check_tensors_dtype_same(data_dtype, value_dtype, op_name): | |||
| f"is not consistent with assigned tensor data type {data_dtype}.") | |||
| @ constexpr | |||
| @constexpr | |||
| def generate_broadcast_shape(shapes, op_name): | |||
| """Generate broadcast shape for a tuple of shape.""" | |||
| if not shapes: | |||
| @@ -428,13 +432,14 @@ def generate_broadcast_shape(shapes, op_name): | |||
| for i, shape in enumerate(shapes): | |||
| logger.debug(f"Broadcasts the {i}th tensor, the shape is {shape}.") | |||
| try: | |||
| broadcast_shape = op_utils.get_broadcast_shape(broadcast_shape, shape, op_name) | |||
| broadcast_shape = op_utils.get_broadcast_shape( | |||
| broadcast_shape, shape, op_name) | |||
| except ValueError as ex: | |||
| raise IndexError(ex) | |||
| return tuple(broadcast_shape) | |||
| @ constexpr | |||
| @constexpr | |||
| def check_two_shapes_need_broadcast(shape_x, shape_y): | |||
| """Check two shapes need broadcast.""" | |||
| error = ValueError(f"For 'tensor setitem with tensor', the value tensor shape " | |||
| @@ -451,14 +456,14 @@ def check_two_shapes_need_broadcast(shape_x, shape_y): | |||
| return True | |||
| @ constexpr | |||
| @constexpr | |||
| def compute_multiples(origin_shape, broadcast_shape): | |||
| """Compute multiples between origin shape with broadcast shape.""" | |||
| len_gap = len(broadcast_shape) - len(origin_shape) | |||
| return broadcast_shape[0:len_gap] + tuple(map(lambda x, y: x // y, broadcast_shape[len_gap:], origin_shape)) | |||
| @ constexpr | |||
| @constexpr | |||
| def compute_new_shape(origin_shape, indexes_shapes_info): | |||
| """Compute new shape between origin shape with final shape.""" | |||
| new_shape = [] | |||
| @@ -470,21 +475,22 @@ def compute_new_shape(origin_shape, indexes_shapes_info): | |||
| return tuple(new_shape) | |||
| @ constexpr | |||
| @constexpr | |||
| def check_sequence_index_type(sequence_index, op_name): | |||
| """check if the item's type of list_index is bool or int""" | |||
| if not all([isinstance(index, (int, bool)) for index in sequence_index]): | |||
| raise IndexError(f"In the {op_name} operation, only support 'integer' or 'boolean' array(list/tuple), " | |||
| f"but got {type(index)} in array") | |||
| for index in sequence_index: | |||
| if not isinstance(index, int): | |||
| raise IndexError(f"In the {op_name} operation, only support 'inter' or 'boolean' array(list/tuple), " | |||
| f"but got {type(index)} in array.") | |||
| @ constexpr | |||
| @constexpr | |||
| def convert_int_to_slice(tuple_index): | |||
| tuple_index_new = tuple(slice(i, i+1, 1) for i in tuple_index) | |||
| return tuple_index_new | |||
| @ constexpr | |||
| @constexpr | |||
| def check_and_transform_int_index(index, shape, op_name): | |||
| if index < -shape or index >= shape: | |||
| raise IndexError(f"In the \"{op_name}\", the index should in the range [-{shape}, {shape-1}] to fit " | |||
| @@ -494,16 +500,20 @@ def check_and_transform_int_index(index, shape, op_name): | |||
| return index | |||
| @ constexpr | |||
| @constexpr | |||
| def transform_sequence_index(sequence_index, shape, op_name): | |||
| """transform list or tuple with integer and boolean to tuple with integer index""" | |||
| bool_count = len(list(filter(lambda index: isinstance(index, bool), sequence_index))) | |||
| int_count = len(list(filter(lambda index: isinstance(index, int), sequence_index)))-bool_count | |||
| bool_count = len( | |||
| list(filter(lambda index: isinstance(index, bool), sequence_index))) | |||
| int_count = len( | |||
| list(filter(lambda index: isinstance(index, int), sequence_index)))-bool_count | |||
| if int_count == 0: | |||
| if bool_count == shape: | |||
| list_index = list(filter(lambda i: sequence_index[i], range(bool_count))) | |||
| list_index = list( | |||
| filter(lambda i: sequence_index[i], range(bool_count))) | |||
| else: | |||
| raise IndexError("The boolean array should have the same length with the corresponding dimensiton") | |||
| raise IndexError( | |||
| "The boolean array should have the same length with the corresponding dimensiton") | |||
| else: | |||
| list_index = [int(index) for index in sequence_index] | |||
| for i, index in enumerate(list_index): | |||
| @@ -512,7 +522,7 @@ def transform_sequence_index(sequence_index, shape, op_name): | |||
| return sub_tuple_index | |||
| @ constexpr | |||
| @constexpr | |||
| def convert_slice_to_tensor(slice_number, final_shape, indexes_shapes_info, op_name): | |||
| """Convert a slice to a tensor.""" | |||
| shape = [] | |||
| @@ -540,7 +550,7 @@ def convert_slice_to_tensor(slice_number, final_shape, indexes_shapes_info, op_n | |||
| return tensor | |||
| @ constexpr | |||
| @constexpr | |||
| def check_shapes_same(value_shapes, op_name): | |||
| """Check if the shapes in the tuple are consistent.""" | |||
| for i, shape in enumerate(value_shapes): | |||
| @@ -550,7 +560,7 @@ def check_shapes_same(value_shapes, op_name): | |||
| return True | |||
| @ constexpr | |||
| @constexpr | |||
| def convert_scalar_to_tensor(data_shape, data_dtype, indices_shape, value, op_type): | |||
| """Convert a scalar to a tensor.""" | |||
| if op_type == SET_ITEM_BY_ONE_TENSOR: | |||
| @@ -563,7 +573,7 @@ def convert_scalar_to_tensor(data_shape, data_dtype, indices_shape, value, op_ty | |||
| f" is not consistent with the assigned tensor data type {data_dtype}.") | |||
| @ constexpr | |||
| @constexpr | |||
| def convert_tuple_of_scalar_to_tensor(data_shape, data_dtype, index_shape, value, op_type): | |||
| """Convert a tuple of scalar to a tensor.""" | |||
| updates_shape = generate_updates_shape(data_shape, index_shape, op_type) | |||
| @@ -575,7 +585,7 @@ def convert_tuple_of_scalar_to_tensor(data_shape, data_dtype, index_shape, value | |||
| return Tensor(np.tile(array, reps)) | |||
| @ constexpr | |||
| @constexpr | |||
| def generate_updates_shape(data_shape, index_shape, op_type): | |||
| """Generate updates shape for 'tensor setitem'.""" | |||
| if op_type == SET_ITEM_BY_ONE_TENSOR: | |||
| @@ -585,7 +595,7 @@ def generate_updates_shape(data_shape, index_shape, op_type): | |||
| return updates_shape | |||
| @ constexpr | |||
| @constexpr | |||
| def check_tuple_index_len(data_rank, tuple_index_len, op_name): | |||
| """Check if the number of index tensor exceeds the dimension of the operated tensor.""" | |||
| if tuple_index_len <= data_rank: | |||
| @@ -594,7 +604,7 @@ def check_tuple_index_len(data_rank, tuple_index_len, op_name): | |||
| f"is greater than the dimension {data_rank} of the operated tensor.") | |||
| @ constexpr | |||
| @constexpr | |||
| def generate_index_info_from_tuple_of_mixed_tensors(data_shape, indexes_types, tensor_indexes_shapes, | |||
| tensor_indexes_dtypes, slice_indexes, op_name): | |||
| """ | |||
| @@ -694,14 +704,14 @@ def scalar_in_sequence(x, y): | |||
| return False | |||
| @ constexpr | |||
| @constexpr | |||
| def get_np_eps(input_dtype): | |||
| nptype = mstype.dtype_to_nptype(input_dtype) | |||
| eps = np.finfo(nptype).eps | |||
| return float(eps) | |||
| @ constexpr | |||
| @constexpr | |||
| def check_number_index_type(number): | |||
| """Check if it is int or bool number""" | |||
| if isinstance(number, bool): | |||
| @@ -712,7 +722,7 @@ def check_number_index_type(number): | |||
| .format(number, type(number))) | |||
| @ constexpr | |||
| @constexpr | |||
| def get_stride_info_from_slice(data_shape, slice_index): | |||
| """Get stride info from a python slice""" | |||
| begin, end, step = get_slice_stride(data_shape[0], slice_index) | |||
| @@ -726,7 +736,7 @@ def get_stride_info_from_slice(data_shape, slice_index): | |||
| return tuple(begin_strides), tuple(end_strides), tuple(step_strides) | |||
| @ constexpr | |||
| @constexpr | |||
| def get_stride_info_from_integer(data_shape, number): | |||
| """Get stride info from a integer""" | |||
| begin_strides = [number] | |||
| @@ -752,7 +762,7 @@ def get_slice_stride(dim_size, index_slice): | |||
| return start, stop, step | |||
| @ constexpr | |||
| @constexpr | |||
| def get_stride_info_from_tuple(data_shape, tuple_index): | |||
| """Get stride info from a tuple""" | |||
| begin_strides, end_strides, step_strides = [], [], [] | |||
| @@ -792,14 +802,14 @@ def get_stride_info_from_tuple(data_shape, tuple_index): | |||
| return tuple(begin_strides), tuple(end_strides), tuple(step_strides), shrink_axis | |||
| @ constexpr | |||
| @constexpr | |||
| def mstype_eq(x, y): | |||
| if x == y: | |||
| return True | |||
| return False | |||
| @ constexpr | |||
| @constexpr | |||
| def scalar_to_tensor(x): | |||
| """Convert a scalar to a tensor""" | |||
| return Tensor(x) | |||