This is my code I am able to execute all lines till the model. fit(X_train, y_train, epochs = 5, validation_data = (X_test, y_test)). I am just wondering if someone knows why and explain to me in detail I assume that my input variables in the line is the problem that I am having but I dint understand why
from tensorflow.keras.preprocessing.text import one_hot,Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense,Flatten,Embedding,Activation,Dropout
from tensorflow.keras.layers import Conv1D, MaxPooling1D, GlobalMaxPooling1D
import numpy as np
from numpy import array
import pandas as pd
from sklearn.model_selection import train_test_split
df = pd.read_csv('IMDB Dataset.csv')
df.head()
df['sentiment'].value_counts()
text = df['review'].tolist()
text
y = df['sentiment']
token = Tokenizer()
token.fit_on_texts(text)
token
token.word_index
vocab_size = len(token.word_index) + 1
vocab_size
encoded_text = token.texts_to_sequences(text)
encoded_text
max_length = 120
X = pad_sequences(encoded_text, maxlen = max_length , padding ='post')
X.shape
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 42,test_size = 0.2,stratify = y)
vec_size = 300
model = Sequential()
model.add(Embedding(vocab_size, vec_size, input_length = max_length))
model.add(Conv1D(64, 8, activation = 'relu'))
model.add(MaxPooling1D(2))
model.add(Dropout(0.2))
model.add(Dense(32, activation = 'relu'))
model.add(Dropout(0.5))
model.add(Dense(16, activation = 'relu'))
model.add(GlobalMaxPooling1D())
model.add(Dense(1, activation = 'sigmoid'))
model.compile(optimizer='adam',loss = 'binary_crossentropy', metrics = ['accuracy'])
%%time
model.fit(X_train, y_train, epochs = 5, validation_data = (X_test, y_test))
from this line ''' model.fit(X_train, y_train, epochs = 5, validation_data = (X_test, y_test))'''
Epoch 1/5
---------------------------------------------------------------------------
UnimplementedError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_23044\3427946316.py in <module>
1 '%%time'
----> 2 model.fit(X_train, y_train, epochs = 5, validation_data = (X_test, y_test))
~\anaconda3\lib\site-packages\keras\utils\traceback_utils.py in error_handler(*args, **kwargs)
68 # To get the full stack trace, call:
69 # `tf.debugging.disable_traceback_filtering()`
---> 70 raise e.with_traceback(filtered_tb) from None
71 finally:
72 del filtered_tb
~\anaconda3\lib\site-packages\tensorflow\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
50 try:
51 ctx.ensure_initialized()
---> 52 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
53 inputs, attrs, num_outputs)
54 except core._NotOkStatusException as e:
UnimplementedError: Graph execution error:
Detected at node 'binary_crossentropy/Cast' defined at (most recent call last):
File "C:\Users\Steven\anaconda3\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Users\Steven\anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel_launcher.py", line 17, in <module>
app.launch_new_instance()
File "C:\Users\Steven\anaconda3\lib\site-packages\traitlets\config\application.py", line 992, in launch_instance
app.start()
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 711, in start
self.io_loop.start()
File "C:\Users\Steven\anaconda3\lib\site-packages\tornado\platform\asyncio.py", line 215, in start
self.asyncio_loop.run_forever()
File "C:\Users\Steven\anaconda3\lib\asyncio\base_events.py", line 601, in run_forever
self._run_once()
File "C:\Users\Steven\anaconda3\lib\asyncio\base_events.py", line 1905, in _run_once
handle._run()
File "C:\Users\Steven\anaconda3\lib\asyncio\events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 510, in dispatch_queue
await self.process_one()
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 499, in process_one
await dispatch(*args)
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 406, in dispatch_shell
await result
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 729, in execute_request
reply_content = await reply_content
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 418, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\Steven\anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 531, in run_cell
return super().run_cell(*args, **kwargs)
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2914, in run_cell
result = self._run_cell(
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2960, in _run_cell
return runner(coro)
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\async_helpers.py", line 78, in _pseudo_sync_runner
coro.send(None)
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3185, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3377, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "C:\Users\Steven\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3457, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "C:\Users\Steven\AppData\Local\Temp\ipykernel_23044\3427946316.py", line 2, in <module>
model.fit(X_train, y_train, epochs = 5, validation_data = (X_test, y_test))
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1650, in fit
tmp_logs = self.train_function(iterator)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1249, in train_function
return step_function(self, iterator)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1233, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1222, in run_step
outputs = model.train_step(data)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1024, in train_step
loss = self.compute_loss(x, y, y_pred, sample_weight)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\training.py", line 1082, in compute_loss
return self.compiled_loss(
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\engine\compile_utils.py", line 265, in __call__
loss_value = loss_obj(y_t, y_p, sample_weight=sw)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\losses.py", line 152, in __call__
losses = call_fn(y_true, y_pred)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\losses.py", line 284, in call
return ag_fn(y_true, y_pred, **self._fn_kwargs)
File "C:\Users\Steven\anaconda3\lib\site-packages\keras\losses.py", line 2165, in binary_crossentropy
y_true = tf.cast(y_true, y_pred.dtype)
Node: 'binary_crossentropy/Cast'
Cast string to float is not supported
[[{{node binary_crossentropy/Cast}}]] [Op:__inference_train_function_23546]
