# 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.elementwise_unary import cast as _cast_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS15.elementwise_unary import clip as _clip_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS15.elementwise_unary import (
inverse as _inverse_iOS15,
)
from coremltools.converters.mil.mil.ops.defs.iOS15.elementwise_unary import log as _log_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS15.elementwise_unary import rsqrt as _rsqrt_iOS15
from coremltools.converters.mil.mil.ops.defs.iOS17 import _IOS17_TARGET
[docs]@register_op(opset_version=_IOS17_TARGET)
class cast(_cast_iOS15):
"""
Cast the input ``x`` to the new type ``dtype``.
The only difference between this version and the iOS 15 :py:class:`~.iOS15.elementwise_unary.cast`
is that it supports int8, uint8, int16, and uint16.
Parameters
----------
x: tensor<[\*d], T> (Required)
dtype: const str (Required)
* Can be one of the following types: ``int8``, ``uint8``, ``int16``, ``uint16``, ``int32``, ``fp16``, ``fp32``, or ``bool``.
Returns
-------
tensor<[\*d], dtype>
* A tensor of the same shape as ``x``, with type ``dtype``.
Attributes
----------
T: i8, ui8, i16, ui16, i32, fp16, fp32, bool.
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"), dtype=TensorInputType(const=True, type_domain=types.str)
)
type_domains = {
"T": (
types.fp16,
types.fp32,
types.int8,
types.uint8,
types.int16,
types.uint16,
types.int32,
types.bool,
),
}
[docs]@register_op(opset_version=_IOS17_TARGET)
class clip(_clip_iOS15):
"""
Clip the values in the input ``x`` to ``[alpha, beta]``, element-wise.
Any values less than ``alpha`` are set to ``alpha``, and any values greater
than ``beta`` are set to ``beta``.
The major difference between this version and the iOS 15 :py:class:`~.iOS15.elementwise_unary.clip`
is that it uses strict validation to ensure that ``alpha < beta``.
Parameters
----------
x: tensor<[\*d], T> (Required)
alpha: const T (Required)
beta: const T (Required)
Returns
-------
tensor<[\*d], T>
* A tensor of the same shape as ``x``.
Attributes
----------
T: fp16, fp32
"""
def type_inference(self):
if self.alpha.val >= self.beta.val:
raise ValueError(
f"The `alpha` value ({self.alpha.val}) should be smaller than `beta` value "
f"({self.beta.val}) in `clip` op."
)
return self.x.sym_type
[docs]@register_op(opset_version=_IOS17_TARGET)
class inverse(_inverse_iOS15):
"""
Return the reciprocal value of the input ``x``, element-wise.
The only difference between this version and the iOS 15 :py:class:`~.iOS15.elementwise_unary.inverse`
is ``epsilon`` may have different dtypes than the inputs/outputs.
Parameters
----------
x: tensor<[\*d], T> (Required)
epsilon: const U (Optional, default=1e-4)
* This is a small constant that is added to the input, before taking its
inverse, for stability.
* ``y = 1 / (x + epsilon)``.
Returns
-------
tensor<[\*d], T>
* A tensor of the same shape as ``x``.
Attributes
----------
T: fp16, fp32
U: fp16, fp32
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
epsilon=TensorInputType(const=True, optional=True, type_domain="U"),
)
type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.fp16, types.fp32),
}
[docs]@register_op(opset_version=_IOS17_TARGET)
class log(_log_iOS15):
"""
Return the natural logarithm value of the input ``x``, element-wise.
The only difference between this version and the iOS 15 :py:class:`~.iOS15.elementwise_unary.log`
is ``epsilon`` may have different dtypes than the inputs/outputs.
Parameters
----------
x: tensor<[\*d], T> (Required)
epsilon: const U (Optional, default=1e-45)
* This is a small constant that is added to the input, before taking log.
* ``y = log(x + epsilon)``.
Returns
-------
tensor<[\*d], T>
* A tensor of the same shape as ``x``.
Attributes
----------
T: fp16, fp32
U: fp16, fp32
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
epsilon=TensorInputType(const=True, optional=True, type_domain="U"),
)
type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.fp16, types.fp32),
}
[docs]@register_op(opset_version=_IOS17_TARGET)
class rsqrt(_rsqrt_iOS15):
"""
Return the reciprocal value of the square root of the input ``x``, element-wise.
The only difference between this version and the iOS 15 :py:class:`~.iOS15.elementwise_unary.rsqrt`
is ``epsilon`` may have different dtypes than the inputs/outputs.
Parameters
----------
x: tensor<[\*d], T> (Required)
epsilon: const U (Optional, default=1e-12)
* This is a small constant that is added to the input, before applying the
``rsqrt`` function, for stability.
* ``y = 1 / sqrt(x + epsilon)``.
Returns
-------
tensor<[\*d], T>
* A tensor of the same shape as ``x``.
Attributes
----------
T: fp16, fp32
U: fp16, fp32
"""
input_spec = InputSpec(
x=TensorInputType(type_domain="T"),
epsilon=TensorInputType(const=True, optional=True, type_domain="U"),
)
type_domains = {
"T": (types.fp16, types.fp32),
"U": (types.fp16, types.fp32),
}