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fadinammour / galaxy2galaxy

Library of models, datasets, and utilities to build generative models for astronomical images.
MIT License
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Adding ParametricCFHT2HST problem #2

Closed fadinammour closed 3 years ago

fadinammour commented 3 years ago

Generate a dataset with CFHT inputs and noiseless HST targets. The noiseless targets allow to perform more accurate measurements on the shape errors. Real galaxy images always contain noise this is why the galaxies of this dataset are parametric.

The chosen profile for the simulated galaxies is the Sersic one.

To do:

fadinammour commented 3 years ago

Since parametric GalSim galaxies do not have noise, the noise power spectra were replaced by mock data with zero values.

fadinammour commented 3 years ago

The first attempt of generating the full dataset failed because the size of the maximal size for the FFT in Galsim. The problem was fixed by augmenting the maximal size. The second attempt ran without outputting any specific problem. However when loading the dataset as follow:

Modes = tf.estimator.ModeKeys
problem128 = problems.problem('attrs2img_cosmos_parametric_cfht2hst')
dset = problem128.dataset(Modes.EVAL, data_dir='~/data/attrs2img_cosmos_parametric_cfht/')
n_batch = 128
dset = dset.batch(n_batch)
iterator = dset.make_one_shot_iterator().get_next()
sess = tf.Session()
batch = sess.run(iterator)

The operation fails and outputs the following error:

WARNING:tensorflow:From <ipython-input-3-750d0e91654d>:2: DatasetV1.make_one_shot_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)`.

---------------------------------------------------------------------------
OutOfRangeError                           Traceback (most recent call last)
/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _do_call(self, fn, *args)
   1364     try:
-> 1365       return fn(*args)
   1366     except errors.OpError as e:

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1349       return self._call_tf_sessionrun(options, feed_dict, fetch_list,
-> 1350                                       target_list, run_metadata)
   1351 

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1442                                             fetch_list, target_list,
-> 1443                                             run_metadata)
   1444 

OutOfRangeError: End of sequence
     [[{{node IteratorGetNext}}]]

During handling of the above exception, another exception occurred:

OutOfRangeError                           Traceback (most recent call last)
<ipython-input-3-750d0e91654d> in <module>
      4 
      5 # Initialize batch
----> 6 batch = sess.run(iterator)
      7 k_batch = 4
      8 

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    954     try:
    955       result = self._run(None, fetches, feed_dict, options_ptr,
--> 956                          run_metadata_ptr)
    957       if run_metadata:
    958         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1178     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1179       results = self._do_run(handle, final_targets, final_fetches,
-> 1180                              feed_dict_tensor, options, run_metadata)
   1181     else:
   1182       results = []

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1357     if handle is None:
   1358       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1359                            run_metadata)
   1360     else:
   1361       return self._do_call(_prun_fn, handle, feeds, fetches)

/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/client/session.py in _do_call(self, fn, *args)
   1382                     '\nsession_config.graph_options.rewrite_options.'
   1383                     'disable_meta_optimizer = True')
-> 1384       raise type(e)(node_def, op, message)
   1385 
   1386   def _extend_graph(self):

OutOfRangeError: End of sequence
     [[node IteratorGetNext (defined at /gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'IteratorGetNext':
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/traitlets/config/application.py", line 664, in launch_instance
    app.start()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/kernelapp.py", line 583, in start
    self.io_loop.start()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/platform/asyncio.py", line 153, in start
    self.asyncio_loop.run_forever()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/asyncio/base_events.py", line 534, in run_forever
    self._run_once()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/asyncio/base_events.py", line 1771, in _run_once
    handle._run()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/asyncio/events.py", line 88, in _run
    self._context.run(self._callback, *self._args)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/ioloop.py", line 743, in _run_callback
    ret = callback()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/gen.py", line 787, in inner
    self.run()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/kernelbase.py", line 361, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/kernelbase.py", line 541, in execute_request
    user_expressions, allow_stdin,
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tornado/gen.py", line 209, in wrapper
    yielded = next(result)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/ipkernel.py", line 300, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/ipykernel/zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 2858, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 2886, in _run_cell
    return runner(coro)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3063, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3254, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-3-750d0e91654d>", line 2, in <module>
    iterator = dset.make_one_shot_iterator().get_next()
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/data/ops/iterator_ops.py", line 426, in get_next
    name=name)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/ops/gen_dataset_ops.py", line 2518, in iterator_get_next
    output_shapes=output_shapes, name=name)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "/gpfslocalsup/pub/anaconda-py3/2019.10/envs/tensorflow-gpu-1.15.2/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

This error is not observed when a subsample of dataset is generated with only 2 shards. In the case of the subsample, the data is loaded successfully.

fadinammour commented 3 years ago

The number of shards didn't match the number of galaxies. The presence of empty shards caused the failure of the data loading. The number of shards was readjusted and the dataset was successfully generated and loaded.