Traceback (most recent call last):


 "/home/jack/envTest.py", line 251, in <module>

collect_step(train_env, agent.collect_policy, replay_buffer)


 "/home/jack/envTest.py", line 209, in collect_step

action_step = policy.action(time_step)


 "/home/jack/tf_agents/policies/tf_policy.py", line 278, in action

step = action_fn(time_step=time_step, policy_state=policy_state, seed=seed)


 "/home/jack/tf_agents/utils/common.py", line 131, in with_check_resource_vars

return fn(*fn_args, **fn_kwargs)


 "/home/jack/tf_agents/policies/epsilon_greedy_policy.py", line 106, in _action

random_action.action)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/util/dispatch.py", line 180, in wrapper

return target(*args, **kwargs)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/ops/array_ops.py", line 3753, in where

return gen_math_ops.select(condition=condition, x=x, y=y, name=name)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_math_ops.py", line 9430, in select

condition, x, y, name=name, ctx=_ctx)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_math_ops.py", line 9462, in select_eager_fallback

_attr_T, _inputs_T = _execute.args_to_matching_eager([x, y], _ctx)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/eager/execute.py", line 257, in args_to_matching_eager

t, dtype, preferred_dtype=default_dtype, ctx=ctx))


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1296, in internal_convert_to_tensor

ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py", line 286, in _constant_tensor_conversion_function

return constant(v, dtype=dtype, name=name)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py", line 227, in constant

allow_broadcast=True)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py", line 235, in _constant_impl

t = convert_to_eager_tensor(value, ctx, dtype)


 "/home/jack/anaconda3/envs/deep/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py", line 96, in convert_to_eager_tensor

return ops.EagerTensor(value, ctx.device_name, dtype)
ValueError: Attempt to convert a value (DictWrapper({'default_asset': <tf.Tensor: id=132834, shape=(1,), dtype=int64, numpy=array([0])>})) with an unsupported type (<class 'tensorflow.python.training.tracking.data_structures._DictWrapper'>) to a Tensor.

Traceback (most recent call last):


 "[the path]/pretrained_word_embeddings.py", line 126, in <module>

embedded_sequences = embedding_layer(sequence_input)


 "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 543, in __call__

self.build(input_shapes[0])


 "/usr/local/lib/python3.5/dist-packages/keras/layers/embeddings.py", line 101, in build

self.set_weights(self.initial_weights)


 "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 966, in set_weights

str(weights)[:50] + '...')
ValueError: You called `set_weights(weights)` on layer "embedding_1" with a
weight list of length 1, but the layer was expecting 0 weights. Provided weights: [array([[ 0.
,
0.
,
0.
, .....