Getting errors trying to calculate R Squared for a Tensorflow Linear Regression model

Question

I have a simple univariate Linear Regression model that I've written using Tensorflow.

I'm trying to calculate the coefficient of determination (R squared) for this model.

I declare R_squared as a tf.Variable (I've also tried declaring it as a placeholder and just declaring it as a normal python variable).

R_squared = tf.variable(0,name = 'R_squared')
prediction = tf.add(tf.multiply(X,W),b)
training_cost = tf.reduce_sum(tf.pow(prediction-Y,2))/(2 * n_samples)
unexplained_cost = tf.reduce_sum(tf.square(tf.subtract(Y,prediction)))
R_squared =  tf.subtract(1.0, tf.divide(unexplained_cost, training_cost))

Later on in the code after running the optimizer, I attempt to print out R_squared.

print ('R squared = ', tf_session.run(R_squared))

But I'm always getting the same error:

Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 1327, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 1306, in _run_fn
    status, run_metadata)
  File "/usr/lib/python3.4/contextlib.py", line 66, in __exit__
    next(self.gen)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder' with dtype float
     [[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "./linear_regression.py", line 126, in <module>
    print ('R squared = ', tf_session.run(R_squared))
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 895, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 1124, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 1321, in _do_run
    options, run_metadata)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py", line 1340, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder' with dtype float
     [[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'Placeholder', defined at:
  File "./linear_regression.py", line 78, in <module>
    X = tf.placeholder('float')
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/array_ops.py", line 1548, in placeholder
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 2094, in _placeholder
    name=name)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 1204, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder' with dtype float
     [[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

I've also tried printing out R_squared.eval() but I still get the same error.

Also, what's the difference between calling the eval method on the tensor object rather than passing it to the session run method?

Any help appreciated.

score 1 · Answer 1 · answered Oct 05 '17 at 09:56

You have defined X as a placeholder somewhere in your code. A placeholder is usually empty unless you assign it a default value or feed it a value using a feed_dict.

For example, try using:

tf_session.run(R_squared, feed_dict={X: 1})

You can obviously substitute the 1 for any other value you desire - you may also use any Python variable instead.

Regarding the difference between eval and run, see this question.

score 0 · Answer 2 · answered Oct 23 '20 at 01:20

I would strongly recommend against using a recipe to calculate this! The examples I've found do not produce consistent results, especially with just one target variable. This gave me enormous headaches!

The correct thing to do is to use tensorflow_addons.metrics.RQsquare(). Tensorflow Add Ons is on PyPi here and the documentation is a part of Tensorflow here. All you have to do is set y_shape to the shape of your output, often it is (1,) for a single output variable.

Getting errors trying to calculate R Squared for a Tensorflow Linear Regression model

2 Answers2