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TensorFlowを使用するのは初めてのことですが、私の問題は解決しやすいかもしれません。 私はシーケンスの次のラベルを予測するためにLSTMCellで作業しようとしています。LSTMCellでdynamic_rnnを呼び出すときのTypeError
ここで私が使用しているコードです：
import tensorflow as tf
max_sequence_length = 1000
vector_length = 1
number_of_classes = 1000
batch_size = 50
num_hidden = 24
# Define graph
data = tf.placeholder(tf.int64, [None, max_sequence_length, vector_length])
# 0 must be a free class so that the mask can work
target = tf.placeholder(tf.int64, [None, max_sequence_length, number_of_classes + 1])
labels = tf.argmax(target, 2)
cell = tf.nn.rnn_cell.LSTMCell(num_hidden, state_is_tuple=True)
をそれから私は、バッチ私はtf.nnを呼び出すしよう
no_of_batches = tf.shape(data)[0]
sequence_lengths = tf.zeros([batch_size])
for i in xrange(max_sequence_length):
data_at_t = tf.squeeze(tf.slice(data, [0,i,0],[-1,1,-1]))
t = tf.scalar_mul(i, tf.ones([batch_size]))
boolean = tf.not_equal(data_at_t, tf.zeros([no_of_batches, batch_size], dtype = tf.int64))
sequence_lengths = tf.select(boolean, t, sequence_lengths)
そして最後に各シーケンスの本当の長さを取得しようとするが、 .dynamic_rnn：
01：次にoutputs, state = tf.nn.dynamic_rnn(
cell = cell,
inputs = data,
sequence_length = max_sequence_length,
dtype = tf.float64
)
、私はTypeError例外を取得します
Traceback (most recent call last):
File "<stdin>", line 5, in <module>
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 830, in dynamic_rnn
dtype=dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 997, in _dynamic_rnn_loop
swap_memory=swap_memory)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1973, in while_loop
result = context.BuildLoop(cond, body, loop_vars)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1860, in BuildLoop
pred, body, original_loop_vars, loop_vars)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1810, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 980, in _time_step
skip_conditionals=True)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 394, in _rnn_step
new_output, new_state = call_cell()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 968, in <lambda>
call_cell = lambda: cell(input_t, state)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 489, in __call__
dtype, self._num_unit_shards)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 323, in _get_concat_variable
sharded_variable = _get_sharded_variable(name, shape, dtype, num_shards)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 353, in _get_sharded_variable
dtype=dtype))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 830, in get_variable
custom_getter=custom_getter)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 673, in get_variable
custom_getter=custom_getter)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 217, in get_variable
validate_shape=validate_shape)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 202, in _true_getter
caching_device=caching_device, validate_shape=validate_shape)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 536, in _get_single_variable
validate_shape=validate_shape)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 211, in __init__
dtype=dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 281, in _init_from_args
self._initial_value = ops.convert_to_tensor(initial_value(),
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 526, in <lambda>
init_val = lambda: initializer(shape.as_list(), dtype=dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/init_ops.py", line 210, in _initializer
dtype, seed=seed)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/random_ops.py", line 235, in random_uniform
minval = ops.convert_to_tensor(minval, dtype=dtype, name="min")
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 621, in convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 180, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 163, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 353, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 290, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int64, got -0.34641016151377546 of type 'float' instead.
このフロートがどこから来ているのか分かりませんが、スクリプト内の他のすべての値は整数です。どうすればこの問題を解決できますか？