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Wenn I random_crop zu crop Bilddatensatz verwenden: tensorflow: Typeerror in random_crop
tf.random_crop(X, [batch_size, 24, 24, 3])
es wirft einen TypeError:
TypeError: Expected int32, got None of type '_Message' instead.
Codes (run 3 Codeblocks unten in Python Terminal kann das Problem reproduzieren):
Ich will zufällig den IM schneiden Alter, bevor es in das Netz einspeisen, so dass ich schreiben random_crop_and_resize:
def random_crop_and_resize():
# batch_size = tf.shape(X)[0]
batch_size, _, _, _ = X.get_shape().as_list()
return tf.image.resize_images \
(tf.random_crop(X, [batch_size, 24, 24, 3]), [32, 32])
und Modellfunktion definiert als:
def my_model(X, y, is_training):
# augmentation: shape of X: [None, 32, 32, 3]
distorted_img = tf.cond(is_training,
random_crop_and_resize, lambda: X)
# ... feed distorted_img into network
dann den Graphen definiert werden:
tf.reset_default_graph()
X = tf.placeholder(tf.float32, [None, 32, 32, 3])
y = tf.placeholder(tf.int64, [None])
is_training = tf.placeholder(tf.bool)
y_out, regularizer = my_model(X, y, is_training)
aber es wirft a TypeError: Expected int32, got None of type '_Message' instead. Wo geht schief?
Weitere Informationen:
Umwelt:
- TensorFlow 1.2 GPU
- 3.6.3 Python von Anaconda
- Ubuntu 14.04.3 LTS
Vollzurückverfolgungs :
--------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-63-67c2d74574b6> in <module>()
77 is_training = tf.placeholder(tf.bool)
78
---> 79 y_out, regularizer = my_model(X, y, is_training)
80
81 # regularization
<ipython-input-63-67c2d74574b6> in my_model(X, y, is_training)
11 # augmentation: shape of X: [None, 32, 32, 3]
12 distorted_img = tf.cond(is_training,
---> 13 random_crop_and_resize, lambda: X)
14
15 regularizer = tf.contrib.layers.l2_regularizer(scale=0.03)
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
287 'in a future version' if date is None else ('after %s' % date),
288 instructions)
--> 289 return func(*args, **kwargs)
290 return tf_decorator.make_decorator(func, new_func, 'deprecated',
291 _add_deprecated_arg_notice_to_docstring(
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py in cond(pred, true_fn, false_fn, strict, name, fn1, fn2)
1812 context_t = CondContext(pred, pivot_1, branch=1)
1813 context_t.Enter()
-> 1814 orig_res_t, res_t = context_t.BuildCondBranch(true_fn)
1815 if orig_res_t is None:
1816 raise ValueError("true_fn must have a return value.")
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py in BuildCondBranch(self, fn)
1687 def BuildCondBranch(self, fn):
1688 """Add the subgraph defined by fn() to the graph."""
-> 1689 original_result = fn()
1690 if original_result is None:
1691 return None, None
<ipython-input-63-67c2d74574b6> in random_crop_and_resize()
5 # batch_size = tf.shape(X)[0]
6 batch_size, _, _, _ = X.get_shape().as_list()
----> 7 return tf.image.resize_images (tf.random_crop(X, [batch_size, 24, 24, 3]), [32, 32])
8
9
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/ops/random_ops.py in random_crop(value, size, seed, name)
297 with ops.name_scope(name, "random_crop", [value, size]) as name:
298 value = ops.convert_to_tensor(value, name="value")
--> 299 size = ops.convert_to_tensor(size, dtype=dtypes.int32, name="size")
300 shape = array_ops.shape(value)
301 check = control_flow_ops.Assert(
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, preferred_dtype)
674 name=name,
675 preferred_dtype=preferred_dtype,
--> 676 as_ref=False)
677
678
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype)
739
740 if ret is None:
--> 741 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
742
743 if ret is NotImplemented:
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
111 as_ref=False):
112 _ = as_ref
--> 113 return constant(v, dtype=dtype, name=name)
114
115
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name, verify_shape)
100 tensor_value = attr_value_pb2.AttrValue()
101 tensor_value.tensor.CopyFrom(
--> 102 tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
103 dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype)
104 const_tensor = g.create_op(
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape)
372 nparray = np.empty(shape, dtype=np_dt)
373 else:
--> 374 _AssertCompatible(values, dtype)
375 nparray = np.array(values, dtype=np_dt)
376 # check to them.
/home/hyh/anaconda3/envs/cs231n/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py in _AssertCompatible(values, dtype)
300 else:
301 raise TypeError("Expected %s, got %s of type '%s' instead." %
--> 302 (dtype.name, repr(mismatch), type(mismatch).__name__))
303
304
TypeError: Expected int32, got None of type '_Message' instead.