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InvalidArgumentError (see above for traceback): tensor_name = linear//weight
print ("Predicted %d, Label: %d" % (classifier.predict(test_data[0]), test_labels[0]))
the below error occurred. InvalidArgumentError (see above for traceback): tensor_name = linear//weight; shape in shape_and_slice spec [1,10] does not match the shape stored in checkpoint: [784,10] [[Node: save/RestoreV2_1 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/cpu:0"](_arg_save/Const_0_0, save/RestoreV2_1/tensor_names, save/RestoreV2_1/shape_and_slices)]]
Although classifier.evaluate(test_data[0:1,:], test_labels[0:1]) is working.. {'accuracy': 1.0, 'global_step': 1000, 'loss': 0.010729363}
Same here.
I got it to work like this:
prediction = classifier.predict(np.array([test_data[0]], dtype=float), as_iterable=False)
print("Predicted %d, Label: %d" % (prediction, test_labels[0]))
@drczuckerman ..works..thanks.