From 2625d541679f4bcce246f04d9e63392037ea92ca Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Fri, 20 Mar 2020 12:22:51 +0100
Subject: [PATCH] Finished legacy Mixins
---
.../base/config/baselines/lda_atnt_legacy.py | 3 +-
bob/bio/base/mixins/legacy.py | 93 ++++++++++---------
2 files changed, 52 insertions(+), 44 deletions(-)
diff --git a/bob/bio/base/config/baselines/lda_atnt_legacy.py b/bob/bio/base/config/baselines/lda_atnt_legacy.py
index 76e859cd..a60c2cd6 100644
--- a/bob/bio/base/config/baselines/lda_atnt_legacy.py
+++ b/bob/bio/base/config/baselines/lda_atnt_legacy.py
@@ -67,7 +67,8 @@ extractor = Pipeline(
),
]
)
-# extractor = dask_it(extractor)
+
+extractor = dask_it(extractor)
from bob.bio.base.pipelines.vanilla_biometrics.biometric_algorithm import (
Distance,
diff --git a/bob/bio/base/mixins/legacy.py b/bob/bio/base/mixins/legacy.py
index 6f34efc6..63e03b90 100644
--- a/bob/bio/base/mixins/legacy.py
+++ b/bob/bio/base/mixins/legacy.py
@@ -11,11 +11,15 @@ from bob.pipelines.mixins import CheckpointMixin, SampleMixin
from sklearn.base import TransformerMixin, BaseEstimator
from sklearn.utils.validation import check_array
from bob.pipelines.sample import Sample, DelayedSample, SampleSet
+from bob.pipelines.utils import is_picklable
import numpy
import logging
import os
+import bob.io.base
+import functools
logger = logging.getLogger(__name__)
+
def scikit_to_bob_supervised(X, Y):
"""
Given an input data ready for :py:method:`scikit.estimator.BaseEstimator.fit`,
@@ -85,30 +89,24 @@ class LegacyProcessorMixin(TransformerMixin):
from bob.pipelines.mixins import CheckpointMixin, SampleMixin
class LegacyAlgorithmMixin(CheckpointMixin,SampleMixin,BaseEstimator):
- """Class that wraps :py:class:`bob.bio.base.algorithm.Algoritm` and
+ """Class that wraps :py:class:`bob.bio.base.algorithm.Algoritm`
- LegacyAlgorithmrMixin.fit maps :py:method:`bob.bio.base.algorithm.Algoritm.train_projector`
+ :py:method:`LegacyAlgorithmrMixin.fit` maps to :py:method:`bob.bio.base.algorithm.Algoritm.train_projector`
- LegacyAlgorithmrMixin.transform maps :py:method:`bob.bio.base.algorithm.Algoritm.project`
+ :py:method:`LegacyAlgorithmrMixin.transform` maps :py:method:`bob.bio.base.algorithm.Algoritm.project`
- THIS HAS TO BE SAMPABLE AND CHECKPOINTABLE
+ .. warning THIS HAS TO BE SAMPABLE AND CHECKPOINTABLE
Example
-------
- Wrapping preprocessor with functtools
- >>> from bob.bio.base.mixins.legacy import LegacyProcessorMixin
- >>> from bob.bio.face.preprocessor import FaceCrop
+ Wrapping LDA algorithm with functtools
+ >>> from bob.bio.base.mixins.legacy import LegacyAlgorithmMixin
+ >>> from bob.bio.base.algorithm import LDA
>>> import functools
- >>> transformer = LegacyProcessorMixin(functools.partial(FaceCrop, cropped_image_size=(10,10)))
+ >>> transformer = LegacyAlgorithmMixin(functools.partial(LDA, use_pinv=True, pca_subspace_dimension=0.90))
- Example
- -------
- Wrapping extractor
- >>> from bob.bio.base.mixins.legacy import LegacyProcessorMixin
- >>> from bob.bio.face.extractor import Linearize
- >>> transformer = LegacyProcessorMixin(Linearize)
Parameters
@@ -121,11 +119,13 @@ class LegacyAlgorithmMixin(CheckpointMixin,SampleMixin,BaseEstimator):
def __init__(self, callable=None, **kwargs):
super().__init__(**kwargs)
self.callable = callable
- self.instance = None
- self.projector_file = os.path.join(self.model_path, "Projector.hdf5")
+ self.instance = None
+ self.projector_file = None
+
def fit(self, X, y=None, **fit_params):
+ self.projector_file = os.path.join(self.model_path, "Projector.hdf5")
if os.path.exists(self.projector_file):
return self
@@ -147,6 +147,21 @@ class LegacyAlgorithmMixin(CheckpointMixin,SampleMixin,BaseEstimator):
def transform(self, X):
+ def _project_save_sample(sample):
+ # Project
+ projected_data = self.instance.project(sample.data)
+
+ #Checkpointing
+ path = self.make_path(sample)
+ bob.io.base.create_directories_safe(os.path.dirname(path))
+ f = bob.io.base.HDF5File(path, "w")
+
+ self.instance.write_feature(projected_data, f)
+ reader = self._get_reader(self.instance.read_feature, path)
+
+ return DelayedSample(reader, parent=sample)
+
+ self.projector_file = os.path.join(self.model_path, "Projector.hdf5")
if not isinstance(X, list):
raise ValueError("It's expected a list, not %s" % type(X))
@@ -155,41 +170,33 @@ class LegacyAlgorithmMixin(CheckpointMixin,SampleMixin,BaseEstimator):
self.instance = self.callable()
self.instance.load_projector(self.projector_file)
- import ipdb; ipdb.set_trace()
-
if isinstance(X[0], Sample) or isinstance(X[0], DelayedSample):
- #samples = []
- for s in X:
- projected_data = self.instance.project(s.data)
-
- #raw_X = [s.data for s in X]
- elif isinstance(X[0], SampleSet):
+ samples = []
+ for sample in X:
+ samples.append(_project_save_sample(sample))
+ return samples
+ elif isinstance(X[0], SampleSet):
+ # Projecting and checkpointing sampleset
sample_sets = []
for sset in X:
-
samples = []
for sample in sset.samples:
+ samples.append(_project_save_sample(sample))
+ sample_sets.append(SampleSet(samples=samples, parent=sset))
+ return sample_sets
- # Project
- projected_data = self.instance.project(sample.data)
-
- #Checkpointing
- path = self.make_path(sample)
- self.instance.write_feature(path)
-
- samples.append(DelayedSample())
-
-
- pass
- #bob.io.base.save(projected_data)
-
-
-
-
- #raw_X = [x.data for s in X for x in s.samples]
else:
raise ValueError("Type not allowed %s" % type(X[0]))
- return self.instance.project(raw_X)
+ def _get_reader(self, reader, path):
+ if(is_picklable(self.instance.read_feature)):
+ return functools.partial(reader, path)
+ else:
+ logger.warning(
+ f"The method {reader} is not picklable. Shiping its unbounded method to `DelayedSample`."
+ )
+ reader = reader.__func__ # The reader object might not be picklable
+ return functools.partial(reader, None, path)
+
--
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