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!6034 [VM][Quant]Add fake quant to ir when run on ascend 

Merge pull request !6034 from chenfei_mindspore/add-quant-delay-in-ascend
This commit is contained in:
mindspore-ci-bot 2020-09-11 18:22:06 +08:00 committed by Gitee
parent 9e8e3e558c 827d5443de
commit a26fdb83ee
1 changed files with 28 additions and 15 deletions
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27
mindspore/nn/layer/quant.py
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@ -372,7 +372,8 @@ class FakeQuantWithMinMax(Cell):
if self.is_ascend: if self.is_ascend:
self.fake_quant_train = quant_fun(num_bits=self.num_bits, self.fake_quant_train = quant_fun(num_bits=self.num_bits,
symmetric=self.symmetric, symmetric=self.symmetric,
narrow_range=self.narrow_range) narrow_range=self.narrow_range,
quant_delay=self.quant_delay)
self.fake_quant_infer = self.fake_quant_train self.fake_quant_infer = self.fake_quant_train
else: else:
quant_fun = partial(quant_fun, quant_fun = partial(quant_fun,
@ -679,15 +680,24 @@ class Conv2dBnWithoutFoldQuant(Cell):
self.group = group self.group = group
self.quant_delay = quant_delay self.quant_delay = quant_delay
weight_shape = [out_channels, in_channels // group, *self.kernel_size]
self.weight = Parameter(initializer(weight_init, weight_shape), name='weight')
self.bias_add = P.BiasAdd() self.bias_add = P.BiasAdd()
if check_bool(has_bias): if check_bool(has_bias):
self.bias = Parameter(initializer(bias_init, [out_channels]), name='bias') self.bias = Parameter(initializer(bias_init, [out_channels]), name='bias')
else: else:
self.bias = None self.bias = None
# initialize convolution op and Parameter
if context.get_context('device_target') == "Ascend" and group > 1:
validator.check_integer('group', group, in_channels, Rel.EQ)
validator.check_integer('group', group, out_channels, Rel.EQ)
self.conv = P.DepthwiseConv2dNative(channel_multiplier=1,
kernel_size=self.kernel_size,
pad_mode=pad_mode,
pad=padding,
stride=self.stride,
dilation=self.dilation)
weight_shape = [1, in_channels, *self.kernel_size]
channel_axis = 1
else:
self.conv = P.Conv2D(out_channel=self.out_channels, self.conv = P.Conv2D(out_channel=self.out_channels,
kernel_size=self.kernel_size, kernel_size=self.kernel_size,
mode=1, mode=1,
@ -696,11 +706,14 @@ class Conv2dBnWithoutFoldQuant(Cell):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
group=self.group) group=self.group)
weight_shape = [out_channels, in_channels // group, *self.kernel_size]
channel_axis = 0
self.weight = Parameter(initializer(weight_init, weight_shape), name='weight')
self.fake_quant_weight = FakeQuantWithMinMax(min_init=-6, self.fake_quant_weight = FakeQuantWithMinMax(min_init=-6,
max_init=6, max_init=6,
ema=False, ema=False,
per_channel=per_channel, per_channel=per_channel,
channel_axis=0, channel_axis=channel_axis,
num_channels=out_channels, num_channels=out_channels,
num_bits=num_bits, num_bits=num_bits,
symmetric=symmetric, symmetric=symmetric,
@ -1009,6 +1022,7 @@ class ActQuant(_QuantActivation):
def get_origin(self): def get_origin(self):
return self.act return self.act
class LeakyReLUQuant(_QuantActivation): class LeakyReLUQuant(_QuantActivation):
r""" r"""
LeakyReLUQuant activation function. Add Fake Quant OP after HSwish OP. LeakyReLUQuant activation function. Add Fake Quant OP after HSwish OP.
@ -1078,7 +1092,6 @@ class LeakyReLUQuant(_QuantActivation):
return self.act return self.act
class HSwishQuant(_QuantActivation): class HSwishQuant(_QuantActivation):
r""" r"""
HSwishQuant activation function. Add Fake Quant OP after HSwish OP. HSwishQuant activation function. Add Fake Quant OP after HSwish OP.