# Copyright (c) 2022, Apple Inc. All rights reserved.
#
# Use of this source code is governed by a BSD-3-clause license that can be
# found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clausefrom
import numpy as np
from coremltools.converters.mil.mil import types
from coremltools.converters.mil.mil.input_type import (DefaultInputs,
InputSpec,
TensorInputType)
from coremltools.converters.mil.mil.operation import (VALUE, Operation,
precondition)
from coremltools.converters.mil.mil.ops.defs._op_reqs import register_op
from coremltools.converters.mil.mil.ops.defs.iOS15.tensor_operation import \
topk as _topk_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS16 import _IOS16_TARGET
[docs]@register_op(opset_version=_IOS16_TARGET)
class fill_like(Operation):
"""
Returns a tensor with the same shape as the input tensor filled with a constant value.
Parameters
----------
ref_tensor: tensor<\*?, T> (Required)
* Input tensor.
value: const<U> (Optional)
* Default is ``0.0``.
* Constant value to fill in.
Returns
-------
tensor<\*?, T>
* Tensor with shape determined by the input tensor.
Attributes
----------
T: fp16, fp32, int32, bool
U: fp16, fp32, int32, bool
"""
input_spec = InputSpec(
ref_tensor=TensorInputType(type_domain="T"),
value=TensorInputType(const=True, optional=True, type_domain="U"),
)
type_domains = {
"T": (types.fp16, types.fp32, types.int32, types.bool),
"U": (types.fp16, types.fp32, types.int32, types.bool),
}
def default_inputs(self):
return DefaultInputs(
value=0.
)
def type_inference(self):
return types.tensor(self.value.dtype, self.ref_tensor.shape)
@precondition(allow=VALUE)
def value_inference(self):
return np.full(shape=self.ref_tensor.shape, fill_value=self.value.val)
[docs]@register_op(opset_version=_IOS16_TARGET)
class topk(_topk_iOS15):
"""
A version of ``topk`` for iOS 16+. This section documents the differences. The following are additional parameters for the iOS 16+ version. For the
rest of the documentation, see `the iOS 15 version of topk <#coremltools.converters.mil.mil.ops.defs.iOS15.tensor_operation.topk>`_.
Parameters
----------
sort: const<bool> (Optional)
* Defaults to ``True``.
* If ``True``, ``top-k`` elements are themselves sorted.
Otherwise, no particular ordering is guaranteed.
return_indices: const<bool> (Optional)
* Defaults to ``True``.
* If ``True``, returns both values and indices. Otherwise, returns only the ``top-k`` values.
Returns
-------
tensor<\*?, T>
* Values of top/bottom ``k`` elements.
tensor<\*?, int32>
* Only returned when ``return_indices = True``
* Indices of the top/bottom ``k`` elements along axis.
Attributes
----------
T: fp32, int32
"""
input_spec = _topk_iOS15.input_spec + InputSpec(
sort=TensorInputType(const=True, optional=True, type_domain=types.bool),
return_indices=TensorInputType(const=True, optional=True, type_domain=types.bool),
)
def default_inputs(self):
return super().default_inputs() + DefaultInputs(sort=True, return_indices=True)
def type_inference(self):
value_type, indices_type = super().type_inference()
if not self.return_indices.val:
return value_type
return value_type, indices_type
@precondition(allow=VALUE)
def value_inference(self):
values, indices = super().value_inference()
if not self.return_indices.val:
return values
return values, indices