hi guys! I hope you are doing well, I got this error in exercise 6 of week 01 assignment even I passed all the tests, I’m really stuck.
LayerError Traceback (most recent call last)
in
2 # Take a look on how the eval_task is inside square brackets and
3 # take that into account for you train_model implementation
----> 4 training_loop = train_model(model, train_task, [eval_task], 100, output_dir_expand)
in train_model(classifier, train_task, eval_task, n_steps, output_dir)
20 eval_tasks=eval_task, # The evaluation task
21 output_dir=output_dir, # The output directory
—> 22 random_seed=31 # Do not modify this random seed in order to ensure reproducibility and for grading purposes.
23 )
24
/opt/conda/lib/python3.7/site-packages/trax/supervised/training.py in init(self, model, tasks, eval_model, eval_tasks, output_dir, checkpoint_at, checkpoint_low_metric, checkpoint_high_metric, permanent_checkpoint_at, eval_at, which_task, n_devices, random_seed, loss_chunk_size, use_memory_efficient_trainer, adasum, callbacks)
305 self._rjust_len = max(map(len, loss_names + metric_names))
306 self._evaluator_per_task = tuple(
→ 307 self._init_evaluator(eval_task) for eval_task in self._eval_tasks)
308
309 if self._output_dir is None:
/opt/conda/lib/python3.7/site-packages/trax/supervised/training.py in (.0)
305 self._rjust_len = max(map(len, loss_names + metric_names))
306 self._evaluator_per_task = tuple(
→ 307 self._init_evaluator(eval_task) for eval_task in self._eval_tasks)
308
309 if self._output_dir is None:
/opt/conda/lib/python3.7/site-packages/trax/supervised/training.py in _init_evaluator(self, eval_task)
364 “”“Initializes the per-task evaluator.”“”
365 model_with_metrics = _model_with_metrics(
→ 366 self._eval_model, eval_task)
367 if self._use_memory_efficient_trainer:
368 return _Evaluator(
/opt/conda/lib/python3.7/site-packages/trax/supervised/training.py in _model_with_metrics(model, eval_task)
1047 “”"
1048 return _model_with_ends(
→ 1049 model, eval_task.metrics, shapes.signature(eval_task.sample_batch)
1050 )
1051
/opt/conda/lib/python3.7/site-packages/trax/supervised/training.py in _model_with_ends(model, end_layers, batch_signature)
1028 # TODO(jonni): Redo this function as part of an initialization refactor?
1029 metrics_layer = tl.Branch(*end_layers)
→ 1030 metrics_input_signature = model.output_signature(batch_signature)
1031 _, _ = metrics_layer.init(metrics_input_signature)
1032
/opt/conda/lib/python3.7/site-packages/trax/layers/base.py in output_signature(self, input_signature)
608 def output_signature(self, input_signature):
609 “”“Returns output signature this layer would give for input_signature.”“”
→ 610 return self._forward_abstract(input_signature)[0] # output only, not state
611
612 def _forward_abstract(self, input_signature):
/opt/conda/lib/python3.7/site-packages/trax/layers/base.py in _forward_abstract(self, input_signature)
640 name, trace = self._name, _short_traceback(skip=7)
641 raise LayerError(name, ‘_forward_abstract’, self._caller, input_signature,
→ 642 trace) from None
643
644 # pylint: disable=protected-access
LayerError: Exception passing through layer Serial (in _forward_abstract):
layer created in file […]/, line 25
layer input shapes: (ShapeDtype{shape:(16, 13), dtype:int32}, ShapeDtype{shape:(16,), dtype:int32}, ShapeDtype{shape:(16,), dtype:int32})
File […]/jax/interpreters/partial_eval.py, line 411, in abstract_eval_fun
lu.wrap_init(fun, params), avals, debug_info)
File […]/jax/interpreters/partial_eval.py, line 1252, in trace_to_jaxpr_dynamic
jaxpr, out_avals, consts = trace_to_subjaxpr_dynamic(fun, main, in_avals)
File […]/jax/interpreters/partial_eval.py, line 1262, in trace_to_subjaxpr_dynamic
ans = fun.call_wrapped(*in_tracers)
File […]/site-packages/jax/linear_util.py, line 166, in call_wrapped
ans = self.f(*args, **dict(self.params, **kwargs))
File […]/site-packages/jax/linear_util.py, line 166, in call_wrapped
ans = self.f(*args, **dict(self.params, **kwargs))
LayerError: Exception passing through layer Serial (in pure_fn):
layer created in file […]/, line 25
layer input shapes: (ShapeDtype{shape:(16, 13), dtype:int32}, ShapeDtype{shape:(16,), dtype:int32}, ShapeDtype{shape:(16,), dtype:int32})
File […]/trax/layers/combinators.py, line 88, in forward
outputs, s = layer.pure_fn(inputs, w, s, rng, use_cache=True)
LayerError: Exception passing through layer Dense_2 (in pure_fn):
layer created in file […]/, line 17
layer input shapes: ShapeDtype{shape:(16, 13), dtype:float32}
File […]/trax/layers/assert_shape.py, line 122, in forward_wrapper
y = forward(self, x, *args, **kwargs)
File […]/trax/layers/core.py, line 96, in forward
return jnp.dot(x, w) + b # Affine map.
File […]/_src/numpy/lax_numpy.py, line 4105, in dot
return lax.dot(a, b, precision=precision)
File […]/_src/lax/lax.py, line 664, in dot
lhs.shape, rhs.shape))
TypeError: Incompatible shapes for dot: got (16, 13) and (15, 2).