# Copyright (c) 2023, 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-Clause
from coremltools.converters.mil.mil import types
from coremltools.converters.mil.mil.input_type import InputSpec, TensorInputType
from coremltools.converters.mil.mil.ops.defs._op_reqs import register_op
from coremltools.converters.mil.mil.ops.defs.iOS15.conv import conv as _conv_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS15.conv import (
conv_transpose as _conv_transpose_iOS15,
)
from coremltools.converters.mil.mil.ops.defs.iOS17 import _IOS17_TARGET
[docs]@register_op(opset_version=_IOS17_TARGET)
class conv(_conv_iOS15):
"""
Perform convolution over input. Supports 1-D, 2-D, and 3-D convolution.
The difference between this version and the iOS 15 :py:class:`~.iOS15.conv.conv` is that the
``weight`` and ``bias`` may have a different dtype than the input/output.
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
weight=TensorInputType(type_domain="U"),
bias=TensorInputType(optional=True, type_domain="U"),
strides=TensorInputType(const=True, optional=True, type_domain=types.int32),
pad_type=TensorInputType(const=True, optional=True, type_domain=types.str),
pad=TensorInputType(const=True, optional=True, type_domain=types.int32),
dilations=TensorInputType(const=True, optional=True, type_domain=types.int32),
groups=TensorInputType(const=True, optional=True, type_domain=types.int32),
)
type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.fp16, types.fp32),
}
[docs]@register_op(opset_version=_IOS17_TARGET)
class conv_transpose(_conv_transpose_iOS15):
"""
Perform transposed convolution (also known as deconvolution and fractionally
stride convolution) over input. ``conv_transpose`` can also be used to compute
the gradient of conv. Supports 1-D, 2-D, and 3-D convolution.
The differences between this version and the iOS 15 :py:class:`~.iOS15.conv.conv_transpose` are:
- ``weight`` and ``bias`` may have a different dtype than the input/output.
- ``weight`` doesn't have to be const.
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
weight=TensorInputType(type_domain="U"),
bias=TensorInputType(optional=True, type_domain="U"),
pad=TensorInputType(const=True, optional=True, type_domain=types.int32),
output_shape=TensorInputType(const=True, optional=True, type_domain=types.int32),
pad_type=TensorInputType(const=True, optional=True, type_domain=types.str),
strides=TensorInputType(const=True, optional=True, type_domain=types.int32),
dilations=TensorInputType(const=True, optional=True, type_domain=types.int32),
groups=TensorInputType(const=True, optional=True, type_domain=types.int32),
)
type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.fp16, types.fp32),
}