RippleNet using Wikidata and Movielens #1014

almudenasanz · 2019-12-17T18:47:17Z

Description

Notebook showcasing RippleNet https://github.com/hwwang55/RippleNet and related files
Uses Movielens dataset and Wikidata as the KG
Reproduces results of https://arxiv.org/abs/1803.03467 for Movielens 1M using Wikidata instead of Microsoft Satori as the KG

Need to update tests

Related Issues

Checklist:

I have followed the contribution guidelines and code style for this project.
I have added tests covering my contributions.
I have updated the documentation accordingly.

miguelgfierro · 2020-01-21T14:19:50Z

@almudenasanz, this is the error I got:

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1333     try:
-> 1334       return fn(*args)
   1335     except errors.OpError as e:

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1318       return self._call_tf_sessionrun(
-> 1319           options, feed_dict, fetch_list, target_list, run_metadata)
   1320 

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1406         self._session, options, feed_dict, fetch_list, target_list,
-> 1407         run_metadata)
   1408 

InvalidArgumentError: indices[6,12] = 22991 is not in [0, 22908)
	 [[{{node embedding_lookup_6}} = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-18-0bb7a5bc8c82> in <module>
      3                train_data=train_data[["user_index", "item", "rating"]].to_numpy(),
      4                ripple_set=ripple_set,
----> 5                show_loss=show_loss)
      6 
      7 print("Took {} seconds for training.".format(train_time.interval))

/data/home/hoaphumanoid/notebooks/repos/recommenders/reco_utils/recommender/ripplenet/model.py in fit(self, n_epoch, batch_size, train_data, ripple_set, show_loss)
    333                 _, loss = self._train(
    334                     self._get_feed_dict(
--> 335                         data=train_data, start=start, end=start + batch_size
    336                     )
    337                 )

/data/home/hoaphumanoid/notebooks/repos/recommenders/reco_utils/recommender/ripplenet/model.py in _train(self, feed_dict)
    273 
    274     def _train(self, feed_dict):
--> 275         return self.sess.run([self.optimizer, self.loss], feed_dict)
    276 
    277     def _return_scores(self, feed_dict):

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    927     try:
    928       result = self._run(None, fetches, feed_dict, options_ptr,
--> 929                          run_metadata_ptr)
    930       if run_metadata:
    931         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1150     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1151       results = self._do_run(handle, final_targets, final_fetches,
-> 1152                              feed_dict_tensor, options, run_metadata)
   1153     else:
   1154       results = []

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1326     if handle is None:
   1327       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328                            run_metadata)
   1329     else:
   1330       return self._do_call(_prun_fn, handle, feeds, fetches)

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1346           pass
   1347       message = error_interpolation.interpolate(message, self._graph)
-> 1348       raise type(e)(node_def, op, message)
   1349 
   1350   def _extend_graph(self):

InvalidArgumentError: indices[6,12] = 22991 is not in [0, 22908)
	 [[node embedding_lookup_6 (defined at ../../reco_utils/recommender/ripplenet/model.py:159)  = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

Caused by op 'embedding_lookup_6', defined at:
  File "/data/anaconda/envs/reco_base/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/data/anaconda/envs/reco_base/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/traitlets/config/application.py", line 664, in launch_instance
    app.start()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 563, in start
    self.io_loop.start()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/platform/asyncio.py", line 148, in start
    self.asyncio_loop.run_forever()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/base_events.py", line 438, in run_forever
    self._run_once()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/base_events.py", line 1451, in _run_once
    handle._run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/events.py", line 145, in _run
    self._callback(*self._args)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/ioloop.py", line 743, in _run_callback
    ret = callback()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 787, in inner
    self.run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 377, in dispatch_queue
    yield self.process_one()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 225, in wrapper
    runner = Runner(result, future, yielded)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 714, in __init__
    self.run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 361, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 541, in execute_request
    user_expressions, allow_stdin,
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 300, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2848, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2874, in _run_cell
    return runner(coro)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3051, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3242, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3319, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-17-b8b001ee6b13>", line 7, in <module>
    seed=seed)
  File "../../reco_utils/recommender/ripplenet/model.py", line 74, in __init__
    self._build_model()
  File "../../reco_utils/recommender/ripplenet/model.py", line 159, in _build_model
    tf.nn.embedding_lookup(self.entity_emb_matrix, self.memories_t[i])
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/embedding_ops.py", line 313, in embedding_lookup
    transform_fn=None)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/embedding_ops.py", line 133, in _embedding_lookup_and_transform
    result = _clip(array_ops.gather(params[0], ids, name=name),
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 2675, in gather
    return gen_array_ops.gather_v2(params, indices, axis, name=name)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3332, in gather_v2
    "GatherV2", params=params, indices=indices, axis=axis, name=name)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
    return func(*args, **kwargs)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
    op_def=op_def)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1770, in __init__
    self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): indices[6,12] = 22991 is not in [0, 22908)
	 [[node embedding_lookup_6 (defined at ../../reco_utils/recommender/ripplenet/model.py:159)  = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

almudenasanz · 2020-01-21T16:13:14Z

@almudenasanz, this is the error I got:

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1333     try:
-> 1334       return fn(*args)
   1335     except errors.OpError as e:

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1318       return self._call_tf_sessionrun(
-> 1319           options, feed_dict, fetch_list, target_list, run_metadata)
   1320 

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1406         self._session, options, feed_dict, fetch_list, target_list,
-> 1407         run_metadata)
   1408 

InvalidArgumentError: indices[6,12] = 22991 is not in [0, 22908)
	 [[{{node embedding_lookup_6}} = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-18-0bb7a5bc8c82> in <module>
      3                train_data=train_data[["user_index", "item", "rating"]].to_numpy(),
      4                ripple_set=ripple_set,
----> 5                show_loss=show_loss)
      6 
      7 print("Took {} seconds for training.".format(train_time.interval))

/data/home/hoaphumanoid/notebooks/repos/recommenders/reco_utils/recommender/ripplenet/model.py in fit(self, n_epoch, batch_size, train_data, ripple_set, show_loss)
    333                 _, loss = self._train(
    334                     self._get_feed_dict(
--> 335                         data=train_data, start=start, end=start + batch_size
    336                     )
    337                 )

/data/home/hoaphumanoid/notebooks/repos/recommenders/reco_utils/recommender/ripplenet/model.py in _train(self, feed_dict)
    273 
    274     def _train(self, feed_dict):
--> 275         return self.sess.run([self.optimizer, self.loss], feed_dict)
    276 
    277     def _return_scores(self, feed_dict):

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    927     try:
    928       result = self._run(None, fetches, feed_dict, options_ptr,
--> 929                          run_metadata_ptr)
    930       if run_metadata:
    931         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1150     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1151       results = self._do_run(handle, final_targets, final_fetches,
-> 1152                              feed_dict_tensor, options, run_metadata)
   1153     else:
   1154       results = []

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1326     if handle is None:
   1327       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328                            run_metadata)
   1329     else:
   1330       return self._do_call(_prun_fn, handle, feeds, fetches)

/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1346           pass
   1347       message = error_interpolation.interpolate(message, self._graph)
-> 1348       raise type(e)(node_def, op, message)
   1349 
   1350   def _extend_graph(self):

InvalidArgumentError: indices[6,12] = 22991 is not in [0, 22908)
	 [[node embedding_lookup_6 (defined at ../../reco_utils/recommender/ripplenet/model.py:159)  = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

Caused by op 'embedding_lookup_6', defined at:
  File "/data/anaconda/envs/reco_base/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/data/anaconda/envs/reco_base/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/traitlets/config/application.py", line 664, in launch_instance
    app.start()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 563, in start
    self.io_loop.start()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/platform/asyncio.py", line 148, in start
    self.asyncio_loop.run_forever()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/base_events.py", line 438, in run_forever
    self._run_once()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/base_events.py", line 1451, in _run_once
    handle._run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/asyncio/events.py", line 145, in _run
    self._callback(*self._args)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/ioloop.py", line 743, in _run_callback
    ret = callback()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 787, in inner
    self.run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 377, in dispatch_queue
    yield self.process_one()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 225, in wrapper
    runner = Runner(result, future, yielded)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 714, in __init__
    self.run()
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 361, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 541, in execute_request
    user_expressions, allow_stdin,
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 300, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2848, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2874, in _run_cell
    return runner(coro)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3051, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3242, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3319, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-17-b8b001ee6b13>", line 7, in <module>
    seed=seed)
  File "../../reco_utils/recommender/ripplenet/model.py", line 74, in __init__
    self._build_model()
  File "../../reco_utils/recommender/ripplenet/model.py", line 159, in _build_model
    tf.nn.embedding_lookup(self.entity_emb_matrix, self.memories_t[i])
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/embedding_ops.py", line 313, in embedding_lookup
    transform_fn=None)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/embedding_ops.py", line 133, in _embedding_lookup_and_transform
    result = _clip(array_ops.gather(params[0], ids, name=name),
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 2675, in gather
    return gen_array_ops.gather_v2(params, indices, axis, name=name)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3332, in gather_v2
    "GatherV2", params=params, indices=indices, axis=axis, name=name)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
    return func(*args, **kwargs)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
    op_def=op_def)
  File "/data/anaconda/envs/reco_base/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1770, in __init__
    self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): indices[6,12] = 22991 is not in [0, 22908)
	 [[node embedding_lookup_6 (defined at ../../reco_utils/recommender/ripplenet/model.py:159)  = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_DOUBLE, _class=["loc:@Adam/Assign_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](entity_emb_matrix/read, _arg_memories_t_1_0_7, embedding_lookup/axis)]]

@miguelgfierro
I had that error in Colab as well, but it was fixed when I selected in Runtime Type the Hardware Accelerator as GPU

miguelgfierro · 2020-01-22T09:34:58Z

@almudenasanz I fixed the error, now everything computes correctly, however, the metrics looks too high, we should take a look

miguelgfierro · 2020-01-22T10:36:57Z

so it looks that the problem is that we are scoring items that are already seen, that's why p@k and r@k are so high. In other algos, we have what we call predict which is for rating, and recommend_k_items, for ranking, an example: https://github.com/microsoft/recommenders/blob/master/reco_utils/recommender/sar/sar_singlenode.py#L433 https://github.com/microsoft/recommenders/blob/master/reco_utils/recommender/surprise/surprise_utils.py. In fact, they have different names depending on the algo, I'll try to fix that on a different PR #1039.

Almudena, can you please take a look at the remove seen example?

miguelgfierro · 2020-01-23T17:47:34Z

hey @almudenasanz, @loomlike found out that in the function convert_rating there is a modification of the original ratings to zero:

train_data.head()

  | user_index | item | rating | original_rating
-- | -- | -- | -- | --
0 | 341 | 1 | 5.0
0 | 3591 | 1 | 4.0
0 | 5725 | 0 | 0.0
0 | 1403 | 0 | 0.0
0 | 1581 | 0 | 0.0

but in movielens, there are no zeros, it goes from 1 to 5. So there has to be some error there

…th top_k_items

almudenasanz · 2020-02-10T11:00:50Z

In introduced new parameters for two functionalities:

Remove items in test that were already seen in train. Although this did not affect our Movielens test because user-item pairs are unique
Keep or remove scores below the threshold when building the ratings dataset. Also added a comment explaining that in the original paper the items below the threshold are removed:

Since MovieLens-1M and Book-Crossing are explicit feedback data, we transform them into implicit feedback where each entry is marked with 1 indicating that the user has rated the item (the threshold of rating is 4 for MovieLens-1M, while no threshold is set for Book-Crossing due to its sparsity), and sample an unwatched set marked as 0 for each user, which is of equal size with the rated ones.

I think we can run it with 1M and it would be ready

miguelgfierro · 2020-02-12T11:48:44Z

hey @almudenasanz I rerun with 100k movielens, still there is an error in the ranking metrics. Please take a look

miguelgfierro · 2020-03-10T10:14:33Z

hey @almudenasanz, this PR has been active since December. I think we should split this PR to have the AUC and accuracy that matches the paper and merge it. Later, on a different PR, we can take a look at the ranking metrics that are not providing good results.
Would this be ok?

almudenasanz · 2020-03-10T14:17:49Z

Hi @miguelgfierro I agree, I would just remove the cells with the precision_at_k and recall_at_k and reproduce with 1M

AdityaSoni19031997 · 2022-10-26T12:56:52Z

Hey @miguelgfierro!

Do we plan to release the Ripple-Net without the precision_at_k and recall_at_k metrics and then fix the ranking metrics by finding the source of error?

Thanks

Edits -> I wish the src was in PyTorch rather than tf 🤐 . Secondly, How to get access to Wiki's KG?

miguelgfierro · 2022-10-27T09:52:47Z

hey @AdityaSoni19031997, answering your questions:

Do we plan to release the Ripple-Net without the precision_at_k and recall_at_k metrics and then fix the ranking metrics by finding the source of error?

that sounds good

I wish the src was in PyTorch rather than tf

This notebook was done years ago when we were using TF1, now we are using TF2. You could either use TF2 or if you want, implement it in PyTorch (there is an implementation https://github.com/qibinc/RippleNet-PyTorch). In general, we prefer PyTorch over TF.

How to get access to Wiki's KG?

The KG is generated from this notebook https://github.com/microsoft/recommenders/blob/ad0bc93142586dd1b856f9bb8629c89947c93235/notebooks/01_prepare_data/wikidata_knowledge_graph.ipynb
but we actually have already generated it:

kg_original = pd.read_csv("https://recodatasets.blob.core.windows.net/wikidata/movielens_{}_wikidata.csv".format(MOVIELENS_DATA_SIZE))
kg_original.head(3)

almudenasanz added 30 commits November 10, 2019 20:29

Initial commit with functioning notebook, missing original files

a4aabfe

modified scripts to avoid intermeditate files

bca8e06

added reference to RippleNet

b025e68

read directly from online source files

27421f8

train method expects numpy arrays

6629614

updated blob name to find all files

73c3641

updated threshold value

e7baa30

new function to retrieve scores

0f175c7

new functions to train and predict

e4856c4

externalise tf session

8bf6917

updated batch_size

50b1646

remove predictions return

865b305

predict to output lists

5177055

updated notebook for new structure and functions

e7d544e

substituted args by explicit parameters

134a3a9

substituted args by explicit parameters

f7fbfb2

substituted args by explicit paramenters in init

355e2f1

functions expect explicit parameters

ea069c9

add exception for lack of data

1499f3d

undo last commit

195f1cf

format and updated seed

9de04d1

remove unused file

5d5baac

function documentation

bf1eadd

added docu

19e5a94

added intro and acc calculation

5c6cd3b

modified eval tu use internal function

c5d87c5

reordered functions

eaff00e

return scores

701c9e9

added data types

a617d77

keep original rating value

2a61af5

code running now

b4c6f10

miguelgfierro added 2 commits January 22, 2020 09:54

some formatting

6367bed

minor edits

3d92ee5

fixed absolute link to code

a6ab41a

almudenasanz and others added 10 commits February 8, 2020 11:48

new function recommend_k_items

6d70cf7

new param to remove or keep negative ratings

03258eb

new params remove negative ratings and new function recommend_k_items

893c5ab

clarification for param remove_negative_ratings

a98322e

transform to numpy matrices internally

641a7c3

internal transform in numpy for train

4004538

missing reference to self.train_data

23e214b

black formatting

c94bbbe

fixed train_data column naming and added precision_at_k evaluation wi…

f71754a

…th top_k_items

Merge branch 'staging' into rippleNet

3f480b8

miguelgfierro added 3 commits February 12, 2020 11:28

edit name to lower case

b372db0

🐛 to_numpy() deprecated in favour of values

2aff810

model run with movielens 100k

8aa4f55

Merge branch 'staging' into rippleNet

ad0bc93

miguelgfierro mentioned this pull request Oct 19, 2022

Simplify eval args #1828

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RippleNet using Wikidata and Movielens #1014

RippleNet using Wikidata and Movielens #1014

almudenasanz commented Dec 17, 2019 •

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AdityaSoni19031997 commented Oct 26, 2022 •

edited

miguelgfierro commented Oct 27, 2022

RippleNet using Wikidata and Movielens #1014

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RippleNet using Wikidata and Movielens #1014

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