Technical problem

benjsce · December 26, 2022, 10:23am

Hello, I installed Tensorflow on my macbook m1 following this method:

jeffheaton/t81_558_deep_learning/blob/master/install/tensorflow-install-conda-mac-metal-jul-2022.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/jeffheaton/t81_558_deep_learning/blob/master/tensorflow-install-mac-metal-jul-2021.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# T81-558: Applications of Deep Neural Networks\n",
    "**Manual Python Setup**\n",
    "* Instructor: [Jeff Heaton](https://sites.wustl.edu/jeffheaton/), McKelvey School of Engineering, [Washington University in St. Louis](https://engineering.wustl.edu/Programs/Pages/default.aspx)\n",
    "* For more information visit the [class website](https://sites.wustl.edu/jeffheaton/t81-558/)."
   ]
  },
  {

This file has been truncated. show original

However, when I create a machine learning algorithm with tensorflow and keras, I get this message:

2022-12-26 11:16:53.762852: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2022-12-26 11:16:53.762897: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) → physical PluggableDevice (device: 0, name: METAL, pci bus id: )

Metal device set to: Apple M1

What can I do to fix this?

Thanks

chunduriv · December 26, 2022, 10:35am

@benjsce,

Welcome to the Tensorflow Forum!

Usually, NUMA is a harmless warning. You can safely ignore the above messages. Here I is an information not a warning.

Is there any issue when running the model?

Thank you!

benjsce · December 26, 2022, 3:31pm

Thanks for your answer.
Yes, I have an error :

when I run this line :

network.fit(train_images, train_labels, epochs=5, batch_size=128)

Jupyter return to me :

Epoch 1/5
2022-12-26 11:17:05.930347: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz

ValueError Traceback (most recent call last)
Cell In[6], line 1
----> 1 network.fit(train_images, train_labels, epochs=5, batch_size=128)

File ~/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/utils/traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs)
67 filtered_tb = _process_traceback_frames(e.traceback)
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

File /var/folders/cd/vqmmmfw1095495p3sfn6zgsh0000gn/T/autograph_generated_fileqjyvjr_7.py:15, in outer_factory..inner_factory..tf__train_function(iterator)
13 try:
14 do_return = True
—> 15 retval = ag_.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
16 except:
17 do_return = False

ValueError: in user code:

File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/training.py", line 1249, in train_function  *
    return step_function(self, iterator)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/training.py", line 1233, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/training.py", line 1222, in run_step  **
    outputs = model.train_step(data)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/training.py", line 1024, in train_step
    loss = self.compute_loss(x, y, y_pred, sample_weight)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/training.py", line 1082, in compute_loss
    return self.compiled_loss(
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/engine/compile_utils.py", line 265, in __call__
    loss_value = loss_obj(y_t, y_p, sample_weight=sw)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/losses.py", line 152, in __call__
    losses = call_fn(y_true, y_pred)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/losses.py", line 284, in call  **
    return ag_fn(y_true, y_pred, **self._fn_kwargs)
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/losses.py", line 2004, in categorical_crossentropy
    return backend.categorical_crossentropy(
File "/Users/benjaminscemama/miniconda3/envs/tensorflow/lib/python3.9/site-packages/keras/backend.py", line 5532, in categorical_crossentropy
    target.shape.assert_is_compatible_with(output.shape)

ValueError: Shapes (None, 1) and (None, 10) are incompatible

I don’t understand…

chunduriv · December 27, 2022, 6:47am

@benjsce,

In order to expedite the trouble-shooting process, please provide a code snippet to reproduce the issue reported here. Thank you!

benjsce · December 27, 2022, 9:49am

Here’s the code :

from keras.datasets import mnist
import numpy as np
import tensorflow as tf
from tensorflow.keras import models
from tensorflow.keras import layers

(train_images, train_labels), (test_images, test_labels) = mnist.load_data()

train_images = train_images.reshape((60000, 28*28))
train_images = train_images.astype(‘float32’) / 255

test_images = test_images.reshape((10000,28*28))
test_images = test_images.astype(‘float32’) /255

network = models.Sequential()
network.add(layers.Dense(512, activation=‘relu’, input_shape=(28*28,)))
network.add(layers.Dense(10, activation=‘softmax’))

network.compile(optimizer=‘rmsprop’,
loss = ‘categorical_crossentropy’,
metrics=[‘accurancy’])

network.fit(train_images, train_labels, epochs=5, batch_size=128)

Thank you!

chunduriv · December 27, 2022, 12:14pm

Here the problem is that train_labels has only one column and the model expects output to have 10 , so it is throwing ValueError: Shapes (None, 1) and (None, 10) are incompatible.

You can convert the data labels (i.e.train_labels and test_labels) to categorical values by performing one-hot encoding using tf.keras.utils.to_categorical as shown below

train_labels = tf.keras.utils.to_categorical(train_labels)
test_labels = tf.keras.utils.to_categorical(test_labels)

Second problem was typo in accuracy

Please refer to the working code below

import numpy as np
import tensorflow as tf
print(tf.__version__)
from tensorflow.keras.datasets import mnist
from tensorflow.keras import models
from tensorflow.keras import layers

(train_images, train_labels), (test_images, test_labels) = mnist.load_data()

train_images = train_images.reshape((60000, 28*28))
train_images = train_images.astype("float32") / 255

test_images = test_images.reshape((10000,28*28,1))
test_images = test_images.astype("float32") /255

# Convert the data labels to categorical values by performing one-hot encoding
train_labels = tf.keras.utils.to_categorical(train_labels)
test_labels = tf.keras.utils.to_categorical(test_labels)

network = models.Sequential()
network.add(layers.Dense(512, activation="relu", input_shape=(28*28,)))
network.add(layers.Dense(10, activation="softmax"))

network.compile(optimizer="adam",loss="categorical_crossentropy" ,metrics=["accuracy"])
network.fit(train_images, train_labels, epochs=5, batch_size=128)

Output:

2.11.0 
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz 
11490434/11490434 [==============================] - 0s 0us/step 
Epoch 1/5 
469/469 [==============================] - 4s 8ms/step - loss: 0.2630 - accuracy: 0.9253 
Epoch 2/5 
469/469 [==============================] - 4s 8ms/step - loss: 0.1084 - accuracy: 0.9681
Epoch 3/5 
469/469 [==============================] - 4s 9ms/step - loss: 0.0706 - accuracy: 0.9795
Epoch 4/5
469/469 [==============================] - 4s 8ms/step - loss: 0.0514 - accuracy: 0.9849
Epoch 5/5 
469/469 [==============================] - 3s 7ms/step - loss: 0.0377 - accuracy: 0.9887

<keras.callbacks.History at 0x7fb5fa45fa60>

Thank you!

benjsce · December 27, 2022, 4:09pm

Here is what jupyter returns to me

2.11.0
Epoch 1/5
2022-12-27 20:21:11.583648: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.
2022-12-27 20:21:11.639007: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x16790f830
2022-12-27 20:21:11.639030: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x16790f830
2022-12-27 20:21:11.640562: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x16790f830
2022-12-27 20:21:11.640575: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x16790f830

NotFoundError Traceback (most recent call last)
Cell In[2], line 25
22 network.add(layers.Dense(10, activation=“softmax”))
24 network.compile(optimizer=“adam”,loss=“categorical_crossentropy” ,metrics=[“accuracy”])
—> 25 network.fit(train_images, train_labels, epochs=5, batch_size=128)

File ~/miniforge3/lib/python3.10/site-packages/keras/utils/traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs)
67 filtered_tb = _process_traceback_frames(e.traceback)
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

File ~/miniforge3/lib/python3.10/site-packages/tensorflow/python/eager/execute.py:52, 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:
55 if name is not None:

NotFoundError: Graph execution error:

Detected at node ‘StatefulPartitionedCall_2’ defined at (most recent call last):
File “/Users/benjaminscemama/miniforge3/lib/python3.10/runpy.py”, line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File “/Users/benjaminscemama/miniforge3/lib/python3.10/runpy.py”, line 86, in _run_code
exec(code, run_globals)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel_launcher.py”, line 17, in
app.launch_new_instance()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/traitlets/config/application.py”, line 992, in launch_instance
app.start()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/kernelapp.py”, line 712, in start
self.io_loop.start()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/tornado/platform/asyncio.py”, line 215, in start
self.asyncio_loop.run_forever()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/asyncio/base_events.py”, line 600, in run_forever
self._run_once()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/asyncio/base_events.py”, line 1896, in _run_once
handle._run()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/asyncio/events.py”, line 80, in _run
self._context.run(self._callback, *self._args)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/kernelbase.py”, line 510, in dispatch_queue
await self.process_one()
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/kernelbase.py”, line 499, in process_one
await dispatch(*args)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/kernelbase.py”, line 406, in dispatch_shell
await result
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/kernelbase.py”, line 730, in execute_request
reply_content = await reply_content
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/ipkernel.py”, line 383, in do_execute
res = shell.run_cell(
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/ipykernel/zmqshell.py”, line 528, in run_cell
return super().run_cell(*args, **kwargs)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 2940, in run_cell
result = self._run_cell(
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 2995, in _run_cell
return runner(coro)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/async_helpers.py”, line 129, in pseudo_sync_runner
coro.send(None)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3194, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3373, in run_ast_nodes
if await self.run_code(code, result, async=asy):
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3433, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File “/var/folders/cd/vqmmmfw1095495p3sfn6zgsh0000gn/T/ipykernel_8524/3824040930.py”, line 25, in
network.fit(train_images, train_labels, epochs=5, batch_size=128)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/engine/training.py”, line 1650, in fit
tmp_logs = self.train_function(iterator)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/engine/training.py”, line 1249, in train_function
return step_function(self, iterator)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/engine/training.py”, line 1233, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/engine/training.py”, line 1222, in run_step
outputs = model.train_step(data)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/engine/training.py”, line 1027, in train_step
self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 527, in minimize
self.apply_gradients(grads_and_vars)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 1140, in apply_gradients
return super().apply_gradients(grads_and_vars, name=name)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 634, in apply_gradients
iteration = self._internal_apply_gradients(grads_and_vars)
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 1166, in _internal_apply_gradients
return tf.internal.distribute.interim.maybe_merge_call(
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 1216, in _distributed_apply_gradients_fn
distribution.extended.update(
File “/Users/benjaminscemama/miniforge3/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py”, line 1211, in apply_grad_to_update_var
return self._update_step_xla(grad, var, id(self._var_key(var)))
Node: ‘StatefulPartitionedCall_2’
could not find registered platform with id: 0x16790f830
[[{{node StatefulPartitionedCall_2}}]] [Op:__inference_train_function_1503]

Thank you!

chunduriv · December 28, 2022, 9:29am

@benjsce,

It seems to be an issue with your tensorflow installation.

Can you install it as suggested Get started with tensorflow-metal ?

Thank you!

benjsce · December 28, 2022, 10:22am

I have already downloaded Tensorflow by this way. I uninstall and install again and I have the same results. I did same for python and I checked Python and Tensorflow version. All it right but Tensorflow doesn’t work.

Thank you

chunduriv · December 28, 2022, 10:40am

@benjsce,

Here the issue with Apple M1 and not with Tensorflow.

Could you please post this issue in the Apple developer forum Apple Developer Forums for quick assistance.

Thank you!

Technical problem

Epoch 1/5 2022-12-26 11:17:05.930347: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz

Epoch 1/5
2022-12-26 11:17:05.930347: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz