From 78144d4cbf76b5c6df9aa57cae3b47e8332f93d2 Mon Sep 17 00:00:00 2001
From: Guy Jacob <guy.jacob@intel.com>
Date: Wed, 6 Nov 2019 17:25:52 +0200
Subject: [PATCH] Bugfix: Deepcopy args when creating ClassifierCompressor
(#421)
Co-authored-by: Bar <29775567+barrh@users.noreply.github.com>
Co-authored-by: Guy Jacob <guy.jacob@intel.com>
---
distiller/apputils/image_classifier.py | 18 ++++++++++--------
distiller/quantization/ptq_greedy_search.py | 1 +
.../auto_compression/amc/parallel-finetune.py | 6 +++---
.../compress_classifier.py | 2 +-
4 files changed, 15 insertions(+), 12 deletions(-)
diff --git a/distiller/apputils/image_classifier.py b/distiller/apputils/image_classifier.py
index 47287fc..451a0ec 100755
--- a/distiller/apputils/image_classifier.py
+++ b/distiller/apputils/image_classifier.py
@@ -14,6 +14,7 @@
# limitations under the License.
#
+import copy
import math
import time
import os
@@ -54,11 +55,11 @@ class ClassifierCompressor(object):
- Classifier training, verification and testing
"""
def __init__(self, args, script_dir):
- self.args = args
- _infer_implicit_args(args)
- self.logdir = _init_logger(args, script_dir)
- _config_determinism(args)
- _config_compute_device(args)
+ self.args = copy.deepcopy(args)
+ _infer_implicit_args(self.args)
+ self.logdir = _init_logger(self.args, script_dir)
+ _config_determinism(self.args)
+ _config_compute_device(self.args)
# Create a couple of logging backends. TensorBoardLogger writes log files in a format
# that can be read by Google's Tensor Board. PythonLogger writes to the Python logger.
@@ -68,12 +69,13 @@ class ClassifierCompressor(object):
self.tflogger = TensorBoardLogger(msglogger.logdir)
self.pylogger = PythonLogger(msglogger)
(self.model, self.compression_scheduler, self.optimizer,
- self.start_epoch, self.ending_epoch) = _init_learner(args)
+ self.start_epoch, self.ending_epoch) = _init_learner(self.args)
# Define loss function (criterion)
- self.criterion = nn.CrossEntropyLoss().to(args.device)
+ self.criterion = nn.CrossEntropyLoss().to(self.args.device)
self.train_loader, self.val_loader, self.test_loader = (None, None, None)
- self.activations_collectors = create_activation_stats_collectors(self.model, *args.activation_stats)
+ self.activations_collectors = create_activation_stats_collectors(
+ self.model, *self.args.activation_stats)
def load_datasets(self):
"""Load the datasets"""
diff --git a/distiller/quantization/ptq_greedy_search.py b/distiller/quantization/ptq_greedy_search.py
index 2d9d8a5..5333c4e 100644
--- a/distiller/quantization/ptq_greedy_search.py
+++ b/distiller/quantization/ptq_greedy_search.py
@@ -434,6 +434,7 @@ if __name__ == "__main__":
args = get_default_args()
args.epochs = float('inf') # hack for args parsing so there's no error in epochs
cc = classifier.ClassifierCompressor(args, script_dir=os.path.dirname(__file__))
+ args = deepcopy(cc.args) # Get back args after modifications in ClassifierCompressor.__init__
eval_data_loader = classifier.load_data(args, load_train=False, load_val=False)
# quant calibration dataloader:
diff --git a/examples/auto_compression/amc/parallel-finetune.py b/examples/auto_compression/amc/parallel-finetune.py
index 80c834f..0dedaaf 100755
--- a/examples/auto_compression/amc/parallel-finetune.py
+++ b/examples/auto_compression/amc/parallel-finetune.py
@@ -178,13 +178,13 @@ def finetune_checkpoint(ckpt_file, gpu, app_args, loaders):
app = classifier.ClassifierCompressor(app_args, script_dir=os.path.dirname(__file__))
app.train_loader, app.val_loader, app.test_loader = loaders
best = [float("-inf"), float("-inf"), float("inf")]
- for epoch in range(app_args.epochs):
- validate = epoch >= math.floor((1-app_args.validate_enable_factor) * app_args.epochs)
+ for epoch in range(app.args.epochs):
+ validate = epoch >= math.floor((1 - app.args.validate_enable_factor) * app.args.epochs)
top1, top5, loss = app.train_validate_with_scheduling(epoch, validate=validate, verbose=False)
if validate:
if top1 > best[0]:
best = [top1, top5, loss]
- if app_args.validate_enable_factor == 0:
+ if app.args.validate_enable_factor == 0:
# We did not validate, so our score is the performance on the Test dataset
return (name, app.test())
return (name, best)
diff --git a/examples/classifier_compression/compress_classifier.py b/examples/classifier_compression/compress_classifier.py
index 93ac393..5108dbf 100755
--- a/examples/classifier_compression/compress_classifier.py
+++ b/examples/classifier_compression/compress_classifier.py
@@ -73,7 +73,7 @@ def main():
app = ClassifierCompressorSampleApp(args, script_dir=os.path.dirname(__file__))
if app.handle_subapps():
return
- init_knowledge_distillation(app.args, app.model, app.compression_scheduler)
+ init_knowledge_distillation(app.args, app.model, app.compression_scheduler)
app.run_training_loop()
# Finally run results on the test set
return app.test()
--
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