class ResnetIdentityBlock(tf.keras.Model):
def __init__(self, kernel_size, filters):
super(ResnetIdentityBlock, self).__init__(name='')
filters1, filters2, filters3 = filters
print("filters1=", filters1)
self.conv2a = tf.keras.layers.Conv2D(filters1, kernel_size=kernel_size, use_bias=False)
self.bn2a = tf.keras.layers.BatchNormalization()
self.conv2b = tf.keras.layers.Conv2D(filters2, kernel_size=kernel_size, padding='same',use_bias=False)
self.bn2b = tf.keras.layers.BatchNormalization()
print("filters3=", filters3)
self.conv2c = tf.keras.layers.Conv2D(filters3, kernel_size=kernel_size,use_bias=False )
self.bn2c = tf.keras.layers.BatchNormalization()
def call(self, input_tensor, training=False):
print("input_tensor shape", input_tensor.shape)
x = self.conv2a(input_tensor)
x = self.bn2a(x, training=training)
x = tf.nn.relu(x)
x = self.conv2b(x)
x = self.bn2b(x, training=training)
x = tf.nn.relu(x)
x = self.conv2c(x)
x = self.bn2c(x, training=training)
x += input_tensor
return tf.nn.relu(x)
block = ResnetIdentityBlock(1, [1, 2, 3])
_ = block(tf.zeros([1, 5, 5, 4]))
输出为：
input_tensor shape (1, 5, 5, 4)
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-200-df6af2fb50f9> in <module>
----> 1 _ = block(tf.zeros([1, 5, 5, 4]))
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
1010 with autocast_variable.enable_auto_cast_variables(
1011 self._compute_dtype_object):
-> 1012 outputs = call_fn(inputs, *args, **kwargs)
1013
1014 if self._activity_regularizer:
<ipython-input-199-94943f82e58b> in call(self, input_tensor, training)
28 x = self.bn2c(x, training=training)
29
---> 30 x += input_tensor
31 return tf.nn.relu(x)
32
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py in binary_op_wrapper(x, y)
1162 with ops.name_scope(None, op_name, [x, y]) as name:
1163 try:
-> 1164 return func(x, y, name=name)
1165 except (TypeError, ValueError) as e:
1166 # Even if dispatching the op failed, the RHS may be a tensor aware
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
199 """Call target, and fall back on dispatchers if there is a TypeError."""
200 try:
--> 201 return target(*args, **kwargs)
202 except (TypeError, ValueError):
203 # Note: convert_to_eager_tensor currently raises a ValueError, not a
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py in _add_dispatch(x, y, name)
1484 return gen_math_ops.add(x, y, name=name)
1485 else:
-> 1486 return gen_math_ops.add_v2(x, y, name=name)
1487
1488
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/gen_math_ops.py in add_v2(x, y, name)
470 return _result
471 except _core._NotOkStatusException as e:
--> 472 _ops.raise_from_not_ok_status(e, name)
473 except _core._FallbackException:
474 pass
/usr/local/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/ops.py in raise_from_not_ok_status(e, name)
6860 message = e.message + (" name: " + name if name is not None else "")
6861 # pylint: disable=protected-access
-> 6862 six.raise_from(core._status_to_exception(e.code, message), None)
6863 # pylint: enable=protected-access
6864
/usr/local/anaconda3/lib/python3.8/site-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: Incompatible shapes: [1,5,5,3] vs. [1,5,5,4] [Op:AddV2]
为什么会出现这样的错误：
Incompatible shapes: [1,5,5,3] vs. [1,5,5,4]
我正在运行 tensorflow 2.0