I am working with gpt2, python 3.9 and tensorflow 2.5 and when connecting to flask (flask run in terminal) I get a following message:
TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
Here is the code in generator.py
#!/usr/bin/env python3
import fire
import json
import os
import numpy as np
import tensorflow.compat.v1 as tf
# import model, sample, encoder
from text_generator import model
from text_generator import sample
from text_generator import encoder
class AI:
def generate_text(self, input_text):
model_name = '117M_Trained'
seed = None,
nsamples = 1
batch_size = 1
length = 150
temperature = 1
top_k = 40
top_p = 1
models_dir = 'models'
self.response = ''
models_dir = os.path.expanduser(os.path.expandvars(models_dir))
if batch_size is None:
batch_size = 1
assert nsamples % batch_size == 0
enc = encoder.get_encoder(model_name, models_dir)
hparams = model.default_hparams()
cur_path = os.path.dirname(__file__) + '/models' + '/' + model_name
with open(cur_path + '/hparams.json') as f:
hparams.override_from_dict(json.load(f))
if length is None:
length = hparams.n_ctx // 2
elif length > hparams.n_ctx:
raise ValueError("Can't get samples longer than window size: %s" % hparams.n_ctx)
with tf.Session(graph=tf.Graph()) as sess:
context = tf.placeholder(tf.int32, [batch_size, None])
np.random.seed(seed)
tf.set_random_seed(seed)
output = sample.sample_sequence(
hparams=hparams, length=length,
context=context,
batch_size=batch_size,
temperature=temperature, top_k=top_k, top_p=top_p
)
saver = tf.train.Saver()
ckpt = tf.train.latest_checkpoint(cur_path)
saver.restore(sess, ckpt)
context_tokens = enc.encode(input_text)
generated = 0
for _ in range(nsamples // batch_size):
out = sess.run(output, feed_dict={
context: [context_tokens for _ in range(batch_size)]
})[:, len(context_tokens):]
for i in range(batch_size):
generated += 1
text = enc.decode(out[i])
self.response = text
return self.response
ai = AI()
text = ai.generate_text('How are you?')
print(text)
Any help is appreciated 🙏 ps I have also added below the entire traceback
* Serving Flask app 'text_generator' (lazy loading)
* Environment: development
* Debug mode: on
2021-09-14 19:58:08.687907: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
File "_mt19937.pyx", line 178, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: 'tuple' object cannot be interpreted as an integer
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/dusandev/miniconda3/bin/flask", line 8, in <module>
sys.exit(main())
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 990, in main
cli.main(args=sys.argv[1:])
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 596, in main
return super().main(*args, **kwargs)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/core.py", line 1062, in main
rv = self.invoke(ctx)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/core.py", line 1668, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/core.py", line 763, in invoke
return __callback(*args, **kwargs)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/decorators.py", line 84, in new_func
return ctx.invoke(f, obj, *args, **kwargs)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/click/core.py", line 763, in invoke
return __callback(*args, **kwargs)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 845, in run_command
app = DispatchingApp(info.load_app, use_eager_loading=eager_loading)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 321, in __init__
self._load_unlocked()
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 346, in _load_unlocked
self._app = rv = self.loader()
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 402, in load_app
app = locate_app(self, import_name, name)
File "/Users/dusandev/miniconda3/lib/python3.9/site-packages/flask/cli.py", line 256, in locate_app
__import__(module_name)
File "/Users/dusandev/Desktop/AI/text_generator/__init__.py", line 2, in <module>
from .routes import generator
File "/Users/dusandev/Desktop/AI/text_generator/routes.py", line 2, in <module>
from .generator import ai
File "/Users/dusandev/Desktop/AI/text_generator/generator.py", line 74, in <module>
text = ai.generate_text('How are you?')
File "/Users/dusandev/Desktop/AI/text_generator/generator.py", line 46, in generate_text
np.random.seed(seed)
File "mtrand.pyx", line 244, in numpy.random.mtrand.RandomState.seed
File "_mt19937.pyx", line 166, in numpy.random._mt19937.MT19937._legacy_seeding
File "_mt19937.pyx", line 186, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
The problem is the line None, in your code. This is causing the tuple (None,) as the input to the np.random.seed(seed). It accepts integer, but you are sending the tuple.