質問編集履歴
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問題解決の糸口が見えてきましたが、未だに改善されません。
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### ＜1/26追記＞
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最下部の内容から進展があったので、記事を更新します。
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問題があるであろう、グラフ作成の部分と実行部分を抜粋します（いくつか変更してます）。
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実行部ではfor文でエポック数を増やしたいのですが、2周目からエラーが出るようです。実行部のfor文をfor i in range(1)とした場合はエラーは生じません。
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**エラー内容は「sess.runにndarrayを入れるな。テンソルを入れてくれ」ということだと思いますが、何故、forの1周目でテンソルだったものが2周目からndarrayに変化してしまうのかがわかりません。**
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```python
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グラフの作成
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g = tf.Graph()
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with g.as_default():
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tf.set_random_seed(123)
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tf_x = tf.placeholder(tf.float32, shape=(None, 4), name='tf_x')
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tf_y = tf.placeholder(tf.int32, shape=(None), name='tf_y')
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oh_y = tf.one_hot(tf_y, 3, dtype=tf.float32, name='oh_y')
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w = tf.Variable(tf.random_normal((4, 3)), name='weight')
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b = tf.Variable(tf.zeros(3), name='bias')
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logits = tf.add(tf.matmul(tf_x, w), b, name='logits')
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prediction = {'probabilities': tf.nn.softmax(logits, name='probabilities'),
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'labels': tf.argmax(logits,1)}
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cost = tf.losses.softmax_cross_entropy(logits=logits, onehot_labels=oh_y)
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# cost = -tf.reduce_sum(oh_y * tf.log(prediction['probabilities']))
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optimizer = tf.train.AdamOptimizer()
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train = optimizer.minimize(cost)
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correct_predictions = tf.equal(prediction['labels'], tf.argmax(oh_y, 1))
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# tf.reduce_meanの中身はfloatにしてあげないと小数点の計算できない
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accuracy = tf.reduce_mean(tf.cast(correct_predictions, tf.float32), name='accuracy')
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init = tf.global_variables_initializer()
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実行
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with tf.Session(graph=g) as sess:
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sess.run(init)
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# ↓のfor文のrange(1)にすると、エラーが生じません。
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for step in range(2):
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_, cost= sess.run([train, cost], feed_dict={tf_x: X_train, tf_y: y_train})
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if (step + 1) % 10 == 0:
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print('Epoch%2d Cost:%.2f' %(step+1, cost))
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print('Prediction Accuracy: %.2f' %(sess.run(accuracy, feed_dict={tf_x: X_test, tf_y: y_test}) * 100))
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```
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### 生じているエラー
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```
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---------------------------------------------------------------------------
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TypeError Traceback (most recent call last)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, fetches, contraction_fn)
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299 self._unique_fetches.append(ops.get_default_graph().as_graph_element(
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--> 300 fetch, allow_tensor=True, allow_operation=True))
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301 except TypeError as e:
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in as_graph_element(self, obj, allow_tensor, allow_operation)
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3489 with self._lock:
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-> 3490 return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _as_graph_element_locked(self, obj, allow_tensor, allow_operation)
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3578 raise TypeError("Can not convert a %s into a %s." % (type(obj).__name__,
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-> 3579 types_str))
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TypeError: Can not convert a float32 into a Tensor or Operation.
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During handling of the above exception, another exception occurred:
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TypeError Traceback (most recent call last)
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<ipython-input-134-171c87a28859> in <module>()
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3 # ↓のfor文のrange(1)にすると、エラーが生じません。
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4 for step in range(2):
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----> 5 _, cost= sess.run([train, cost], feed_dict={tf_x: X_train, tf_y: y_train})
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6 if (step + 1) % 10 == 0:
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7 print('Epoch%2d Cost:%.2f' %(step+1, cost))
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
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927 try:
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928 result = self._run(None, fetches, feed_dict, options_ptr,
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--> 929 run_metadata_ptr)
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930 if run_metadata:
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931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
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1135 # Create a fetch handler to take care of the structure of fetches.
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1136 fetch_handler = _FetchHandler(
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-> 1137 self._graph, fetches, feed_dict_tensor, feed_handles=feed_handles)
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1139 # Run request and get response.
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, graph, fetches, feeds, feed_handles)
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469 """
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470 with graph.as_default():
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--> 471 self._fetch_mapper = _FetchMapper.for_fetch(fetches)
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472 self._fetches = []
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473 self._targets = []
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in for_fetch(fetch)
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259 elif isinstance(fetch, (list, tuple)):
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260 # NOTE(touts): This is also the code path for namedtuples.
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--> 261 return _ListFetchMapper(fetch)
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262 elif isinstance(fetch, collections.Mapping):
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263 return _DictFetchMapper(fetch)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, fetches)
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368 """
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369 self._fetch_type = type(fetches)
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--> 370 self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
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371 self._unique_fetches, self._value_indices = _uniquify_fetches(self._mappers)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in <listcomp>(.0)
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368 """
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369 self._fetch_type = type(fetches)
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--> 370 self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
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371 self._unique_fetches, self._value_indices = _uniquify_fetches(self._mappers)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in for_fetch(fetch)
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269 if isinstance(fetch, tensor_type):
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270 fetches, contraction_fn = fetch_fn(fetch)
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--> 271 return _ElementFetchMapper(fetches, contraction_fn)
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272 # Did not find anything.
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273 raise TypeError('Fetch argument %r has invalid type %r' % (fetch,
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302 raise TypeError('Fetch argument %r has invalid type %r, '
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303 'must be a string or Tensor. (%s)' %
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--> 304 (fetch, type(fetch), str(e)))
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305 except ValueError as e:
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306 raise ValueError('Fetch argument %r cannot be interpreted as a '
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TypeError: Fetch argument 5.690171 has invalid type <class 'numpy.float32'>, must be a string or Tensor. (Can not convert a float32 into a Tensor or Operation.)
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```
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＜以下、更新前の原文＞
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[GitHubの記事](https://github.com/kujirahand/book-mlearn-gyomu/blob/master/src/ch5/iris/tf-iris.py)を参考にTensorFlowでアヤメの分類問題をやっているのですが、恐らくデータ型のエラーがどうしても解消できません。
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コスト関数の最適化のとこでエラーが出ていますが、上の記事と見合わせても、データ型的にどこが間違えているのかがわかりません。
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@@ -128,180 +408,12 @@
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```
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### 生じているエラー
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### 生じているエラー（追記時に字数が足りなくなったので削りました）
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```ここに言語を入力
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---------------------------------------------------------------------------
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TypeError Traceback (most recent call last)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, fetches, contraction_fn)
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299 self._unique_fetches.append(ops.get_default_graph().as_graph_element(
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--> 300 fetch, allow_tensor=True, allow_operation=True))
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301 except TypeError as e:
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in as_graph_element(self, obj, allow_tensor, allow_operation)
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3489 with self._lock:
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-> 3490 return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _as_graph_element_locked(self, obj, allow_tensor, allow_operation)
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3578 raise TypeError("Can not convert a %s into a %s." % (type(obj).__name__,
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-> 3579 types_str))
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TypeError: Can not convert a float32 into a Tensor or Operation.
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During handling of the above exception, another exception occurred:
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TypeError Traceback (most recent call last)
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<ipython-input-1-c6d4748fd830> in <module>()
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53 for step in range(300):
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---> 54 _, cost, accuracy = sess.run([train, cost, accuracy], feed_dict={tf_x: X_train, tf_y: y_train})
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55 if (step + 1) % 10 == 0:
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56 print('Epoch%2d Cost:%.2f Accuracy:%.2f%%' %(step+1, cost, accuracy*100))
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190
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191
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192
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193
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194
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195
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927 try:
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196
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197
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928 result = self._run(None, fetches, feed_dict, options_ptr,
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198
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199
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--> 929 run_metadata_ptr)
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200
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201
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930 if run_metadata:
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202
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203
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931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
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204
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205
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206
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207
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
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208
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209
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1135 # Create a fetch handler to take care of the structure of fetches.
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210
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211
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1136 fetch_handler = _FetchHandler(
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213
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-> 1137 self._graph, fetches, feed_dict_tensor, feed_handles=feed_handles)
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215
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1138
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216
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217
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1139 # Run request and get response.
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218
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219
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220
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221
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, graph, fetches, feeds, feed_handles)
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222
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223
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469 """
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224
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225
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470 with graph.as_default():
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226
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227
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--> 471 self._fetch_mapper = _FetchMapper.for_fetch(fetches)
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228
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229
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472 self._fetches = []
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230
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231
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473 self._targets = []
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232
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233
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234
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235
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in for_fetch(fetch)
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236
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237
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259 elif isinstance(fetch, (list, tuple)):
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238
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239
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260 # NOTE(touts): This is also the code path for namedtuples.
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240
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241
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--> 261 return _ListFetchMapper(fetch)
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242
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243
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262 elif isinstance(fetch, collections.Mapping):
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244
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245
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263 return _DictFetchMapper(fetch)
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246
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247
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248
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249
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, fetches)
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250
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251
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368 """
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252
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253
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369 self._fetch_type = type(fetches)
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254
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255
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--> 370 self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
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256
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257
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371 self._unique_fetches, self._value_indices = _uniquify_fetches(self._mappers)
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258
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259
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372
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260
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261
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262
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263
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/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in <listcomp>(.0)
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264
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265
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-
368 """
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266
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-
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267
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369 self._fetch_type = type(fetches)
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268
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-
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269
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-
--> 370 self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
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270
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-
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271
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-
371 self._unique_fetches, self._value_indices = _uniquify_fetches(self._mappers)
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272
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-
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273
|
-
372
|
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274
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-
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275
|
-
|
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276
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-
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277
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-
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in for_fetch(fetch)
|
|
278
|
-
|
|
279
|
-
269 if isinstance(fetch, tensor_type):
|
|
280
|
-
|
|
281
|
-
270 fetches, contraction_fn = fetch_fn(fetch)
|
|
282
|
-
|
|
283
|
-
--> 271 return _ElementFetchMapper(fetches, contraction_fn)
|
|
284
|
-
|
|
285
|
-
272 # Did not find anything.
|
|
286
|
-
|
|
287
|
-
273 raise TypeError('Fetch argument %r has invalid type %r' % (fetch,
|
|
288
|
-
|
|
289
|
-
|
|
290
|
-
|
|
291
|
-
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in __init__(self, fetches, contraction_fn)
|
|
292
|
-
|
|
293
|
-
302 raise TypeError('Fetch argument %r has invalid type %r, '
|
|
294
|
-
|
|
295
|
-
303 'must be a string or Tensor. (%s)' %
|
|
296
|
-
|
|
297
|
-
--> 304 (fetch, type(fetch), str(e)))
|
|
298
|
-
|
|
299
|
-
305 except ValueError as e:
|
|
300
|
-
|
|
301
|
-
306 raise ValueError('Fetch argument %r cannot be interpreted as a '
|
|
302
|
-
|
|
303
|
-
|
|
304
|
-
|
|
305
417
|
TypeError: Fetch argument 682.8205 has invalid type <class 'numpy.float32'>, must be a string or Tensor. (Can not convert a float32 into a Tensor or Operation.)
|
|
306
418
|
|
|
307
419
|
```
|