TypeError: Error converting shape to a TensorShape: int() argument must be a string, a bytes-like object or a number, not 'tuple'

[ronseg1]

While trying to run the code: https://github.com/ShuaiW/teach-machine-to-trade/blob/master/run.py with: python run.py --mode train

I get the error:

Traceback (most recent call last): File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\eager\execute.py", line 141, in make_shape shape = tensor_shape.as_shape(v) File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 946, in as_shape return TensorShape(shape) File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 541, in init self._dims = [as_dimension(d) for d in dims_iter] File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 541, in self._dims = [as_dimension(d) for d in dims_iter] File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 482, in as_dimension return Dimension(value) File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 37, in init self._value = int(value) TypeError: int() argument must be a string, a bytes-like object or a number, not 'tuple'

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "run.py", line 38, in agent = DQNAgent(state_size, action_size) File "C:\Users\i\Q-Learning-for-Trading-master\agent.py", line 18, in init self.model = mlp(state_size, action_size) File "C:\Users\i\Q-Learning-for-Trading-master\model.py", line 11, in mlp model.add(Dense(n_neuron_per_layer, input_dim=n_obs, activation=activation)) File "C:\Users\i\Anaconda3\lib\site-packages\keras\engine\sequential.py", line 161, in add name=layer.name + '_input') File "C:\Users\i\Anaconda3\lib\site-packages\keras\engine\input_layer.py", line 178, in Input input_tensor=tensor) File "C:\Users\i\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "C:\Users\i\Anaconda3\lib\site-packages\keras\engine\input_layer.py", line 87, in init name=self.name) File "C:\Users\i\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 517, in placeholder x = tf.placeholder(dtype, shape=shape, name=name) File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1734, in placeholder return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name) File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5925, in placeholder shape = _execute.make_shape(shape, "shape") File "C:\Users\i\Anaconda3\lib\site-packages\tensorflow\python\eager\execute.py", line 143, in make_shape raise TypeError("Error converting %s to a TensorShape: %s." % (arg_name, e)) TypeError: Error converting shape to a TensorShape: int() argument must be a string, a bytes-like object or a number, not 'tuple'.

---

I am using python 3.7 instead of python 2.7

Thanks in advance

[jolivaresc]

In run.py I've changed this line: state_size = env.observation_space.shape to this state_size = env.observation_space.shape[0][0]

next_state, reward, done, info = env.step(action) to next_state, reward, done, info = env._step(action)

Also in envs.py: action_vec = action_combo[action] -> action_vec = list(action_combo)[action]

With this changes I managed to run the script.

[jolivaresc]

In run.py I've changed this line: state_size = env.observation_space.shape to this state_size = env.observation_space.shape[0][0]

next_state, reward, done, info = env.step(action) to next_state, reward, done, info = env._step(action)

Also in envs.py: action_vec = action_combo[action] -> action_vec = list(action_combo)[action]

With this changes I managed to run the script.

I added a new method in the agent class agent.py so now script model.py it is not necessary

self.model=self.brain()
...
def brain(self):
        model = tf.keras.models.Sequential([
            tf.keras.layers.Dense(units=20,
                                  #input_shape=(self.state_size,),
                                  activation=tf.nn.tanh),
            tf.keras.layers.Dense(units=20, activation=tf.nn.tanh),
            tf.keras.layers.Dense(units=self.action_size)
        ])
        model.compile(loss="mse",
                      optimizer=tf.keras.optimizers.RMSprop(1e-3))
        return model

[ronseg1]

In run.py I've changed this line: state_size = env.observation_space.shape to this state_size = env.observation_space.shape[0][0]

next_state, reward, done, info = env.step(action) to next_state, reward, done, info = env._step(action)

Also in envs.py: action_vec = action_combo[action] -> action_vec = list(action_combo)[action]

With this changes I managed to run the script.

Hi It seems that my mistake was using the current version of gym instead of gym==0.9.4. , so after reinstall gym and convert the script to python 3 with 2to3 it works fine. Thanks