The dimension seems to be the issue. Should the input be in numpy array?
import tensorflow as tf
import numpy as np
X = np.array([-7.0, 3.0, 10.0, 20.0, 30.0])
y = np.array([3.0, 13.0, 23.0, 33.0, 43.0])
x_train = tf.constant(X)
y_train = tf.constant(y)
model = tf.keras.Sequential([
tf.keras.layers.Dense(100, activation="relu"),
tf.keras.layers.Dense(100, activation="relu"),
tf.keras.layers.Dense(100, activation="relu"),
tf.keras.layers.Dense(1, activation=None)
])
# Compile the model
model.compile(loss=tf.keras.losses.mae, optimizer=tf.keras.optimizers.Adam(lr=0.001))
# fit the model
model.fit(x_train, y_train, epochs=5)
ValueError: Exception encountered when calling layer "sequential_2" (type Sequential). Input 0 of layer "dense_8" is incompatible with the layer: expected min_ndim=2, found ndim=1. Full shape received: (None,)
Epoch 1/5
------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-19-fc6fe32aa384> in <module>()
1 # fit the model
----> 2 model.fit(x_train, y_train, epochs=5)
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in
autograph_handler(*args, **kwargs)
1145 except Exception as e: # pylint:disable=broad-except
1146 if hasattr(e, "ag_error_metadata"):
-> 1147 raise e.ag_error_metadata.to_exception(e)
1148 else:
1149 raise
ValueError: in user code:
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in
train_function *
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in
step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step
**
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 859, in
train_step
y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 67, in
error_handler
raise e.with_traceback(filtered_tb) from None
File "/usr/local/lib/python3.7/dist-packages/keras/engine/input_spec.py", line 228, in
assert_input_compatibility
raise ValueError(f'Input {input_index} of layer "{layer_name}" '
ValueError: Exception encountered when calling layer "sequential_2" (type Sequential).
Input 0 of layer "dense_8" is incompatible with the layer: expected min_ndim=2, found ndim=1.
Full shape received: (None,)
Call arguments received:
• inputs=tf.Tensor(shape=(None,), dtype=float64)
• training=True
• mask=None
