From 4b3214c0a1c7e4526029bc14557ad26820d03c71 Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Wed, 11 Nov 2020 14:40:04 -0800 Subject: [PATCH] Internal change PiperOrigin-RevId: 341913626 --- .../configs/experiments/retinanet/coco_spinenet143_tpu.yaml | 1 - .../configs/experiments/retinanet/coco_spinenet190_tpu.yaml | 1 - .../configs/experiments/retinanet/coco_spinenet49_tpu.yaml | 1 - .../configs/experiments/retinanet/coco_spinenet96_tpu.yaml | 1 - official/vision/beta/configs/image_classification.py | 1 - official/vision/beta/configs/maskrcnn.py | 1 - official/vision/beta/configs/retinanet.py | 1 - official/vision/beta/configs/semantic_segmentation.py | 1 - official/vision/beta/configs/video_classification.py | 1 - official/vision/beta/tasks/image_classification.py | 5 ----- official/vision/beta/tasks/maskrcnn.py | 5 ----- official/vision/beta/tasks/retinanet.py | 5 ----- official/vision/beta/tasks/semantic_segmentation.py | 5 ----- official/vision/beta/tasks/video_classification.py | 5 ----- 14 files changed, 34 deletions(-) diff --git a/official/vision/beta/configs/experiments/retinanet/coco_spinenet143_tpu.yaml b/official/vision/beta/configs/experiments/retinanet/coco_spinenet143_tpu.yaml index 919163f2c..25c8c1732 100644 --- a/official/vision/beta/configs/experiments/retinanet/coco_spinenet143_tpu.yaml +++ b/official/vision/beta/configs/experiments/retinanet/coco_spinenet143_tpu.yaml @@ -4,7 +4,6 @@ runtime: mixed_precision_dtype: 'bfloat16' task: annotation_file: '/readahead/200M/placer/prod/home/snaggletooth/test/data/coco/instances_val2017.json' - gradient_clip_norm: 10.0 losses: l2_weight_decay: 4.0e-05 model: diff --git a/official/vision/beta/configs/experiments/retinanet/coco_spinenet190_tpu.yaml b/official/vision/beta/configs/experiments/retinanet/coco_spinenet190_tpu.yaml index 69c9c02bc..9de3acf2c 100644 --- a/official/vision/beta/configs/experiments/retinanet/coco_spinenet190_tpu.yaml +++ b/official/vision/beta/configs/experiments/retinanet/coco_spinenet190_tpu.yaml @@ -3,7 +3,6 @@ runtime: mixed_precision_dtype: 'bfloat16' task: annotation_file: '/readahead/200M/placer/prod/home/snaggletooth/test/data/coco/instances_val2017.json' - gradient_clip_norm: 0.0 losses: l2_weight_decay: 4.0e-05 model: diff --git a/official/vision/beta/configs/experiments/retinanet/coco_spinenet49_tpu.yaml b/official/vision/beta/configs/experiments/retinanet/coco_spinenet49_tpu.yaml index b97867b6c..105ba941b 100644 --- a/official/vision/beta/configs/experiments/retinanet/coco_spinenet49_tpu.yaml +++ b/official/vision/beta/configs/experiments/retinanet/coco_spinenet49_tpu.yaml @@ -4,7 +4,6 @@ runtime: mixed_precision_dtype: 'bfloat16' task: annotation_file: '/readahead/200M/placer/prod/home/snaggletooth/test/data/coco/instances_val2017.json' - gradient_clip_norm: 0.0 losses: l2_weight_decay: 4.0e-05 model: diff --git a/official/vision/beta/configs/experiments/retinanet/coco_spinenet96_tpu.yaml b/official/vision/beta/configs/experiments/retinanet/coco_spinenet96_tpu.yaml index 68cb946ab..daa48cce8 100644 --- a/official/vision/beta/configs/experiments/retinanet/coco_spinenet96_tpu.yaml +++ b/official/vision/beta/configs/experiments/retinanet/coco_spinenet96_tpu.yaml @@ -4,7 +4,6 @@ runtime: mixed_precision_dtype: 'bfloat16' task: annotation_file: '/readahead/200M/placer/prod/home/snaggletooth/test/data/coco/instances_val2017.json' - gradient_clip_norm: 0.0 losses: l2_weight_decay: 4.0e-05 model: diff --git a/official/vision/beta/configs/image_classification.py b/official/vision/beta/configs/image_classification.py index bfee72386..9d4da5920 100644 --- a/official/vision/beta/configs/image_classification.py +++ b/official/vision/beta/configs/image_classification.py @@ -70,7 +70,6 @@ class ImageClassificationTask(cfg.TaskConfig): validation_data: DataConfig = DataConfig(is_training=False) losses: Losses = Losses() evaluation: Evaluation = Evaluation() - gradient_clip_norm: float = 0.0 init_checkpoint: Optional[str] = None init_checkpoint_modules: str = 'all' # all or backbone diff --git a/official/vision/beta/configs/maskrcnn.py b/official/vision/beta/configs/maskrcnn.py index ef34a2393..58ed92fd8 100644 --- a/official/vision/beta/configs/maskrcnn.py +++ b/official/vision/beta/configs/maskrcnn.py @@ -207,7 +207,6 @@ class MaskRCNNTask(cfg.TaskConfig): init_checkpoint: Optional[str] = None init_checkpoint_modules: str = 'all' # all or backbone annotation_file: Optional[str] = None - gradient_clip_norm: float = 0.0 per_category_metrics: bool = False # If set, we only use masks for the specified class IDs. allowed_mask_class_ids: Optional[List[int]] = None diff --git a/official/vision/beta/configs/retinanet.py b/official/vision/beta/configs/retinanet.py index 2c2f93a95..4e339bf26 100644 --- a/official/vision/beta/configs/retinanet.py +++ b/official/vision/beta/configs/retinanet.py @@ -128,7 +128,6 @@ class RetinaNetTask(cfg.TaskConfig): init_checkpoint: Optional[str] = None init_checkpoint_modules: str = 'all' # all or backbone annotation_file: Optional[str] = None - gradient_clip_norm: float = 0.0 per_category_metrics: bool = False diff --git a/official/vision/beta/configs/semantic_segmentation.py b/official/vision/beta/configs/semantic_segmentation.py index fbf499224..146bff0f1 100644 --- a/official/vision/beta/configs/semantic_segmentation.py +++ b/official/vision/beta/configs/semantic_segmentation.py @@ -87,7 +87,6 @@ class SemanticSegmentationTask(cfg.TaskConfig): train_data: DataConfig = DataConfig(is_training=True) validation_data: DataConfig = DataConfig(is_training=False) losses: Losses = Losses() - gradient_clip_norm: float = 0.0 init_checkpoint: Optional[str] = None init_checkpoint_modules: Union[ str, List[str]] = 'all' # all, backbone, and/or decoder diff --git a/official/vision/beta/configs/video_classification.py b/official/vision/beta/configs/video_classification.py index 418e6d802..3d4b7aecb 100644 --- a/official/vision/beta/configs/video_classification.py +++ b/official/vision/beta/configs/video_classification.py @@ -97,7 +97,6 @@ class VideoClassificationTask(cfg.TaskConfig): train_data: DataConfig = DataConfig(is_training=True) validation_data: DataConfig = DataConfig(is_training=False) losses: Losses = Losses() - gradient_clip_norm: float = -1.0 def add_trainer(experiment: cfg.ExperimentConfig, diff --git a/official/vision/beta/tasks/image_classification.py b/official/vision/beta/tasks/image_classification.py index 07d6fd246..e0b826467 100644 --- a/official/vision/beta/tasks/image_classification.py +++ b/official/vision/beta/tasks/image_classification.py @@ -180,11 +180,6 @@ class ImageClassificationTask(base_task.Task): if isinstance( optimizer, tf.keras.mixed_precision.LossScaleOptimizer): grads = optimizer.get_unscaled_gradients(grads) - - # Apply gradient clipping. - if self.task_config.gradient_clip_norm > 0: - grads, _ = tf.clip_by_global_norm( - grads, self.task_config.gradient_clip_norm) optimizer.apply_gradients(list(zip(grads, tvars))) logs = {self.loss: loss} diff --git a/official/vision/beta/tasks/maskrcnn.py b/official/vision/beta/tasks/maskrcnn.py index 5153b6b2c..f68067a19 100644 --- a/official/vision/beta/tasks/maskrcnn.py +++ b/official/vision/beta/tasks/maskrcnn.py @@ -280,11 +280,6 @@ class MaskRCNNTask(base_task.Task): # Scales back gradient when LossScaleOptimizer is used. if isinstance(optimizer, tf.keras.mixed_precision.LossScaleOptimizer): grads = optimizer.get_unscaled_gradients(grads) - - # Apply gradient clipping. - if self.task_config.gradient_clip_norm > 0: - grads, _ = tf.clip_by_global_norm( - grads, self.task_config.gradient_clip_norm) optimizer.apply_gradients(list(zip(grads, tvars))) logs = {self.loss: losses['total_loss']} diff --git a/official/vision/beta/tasks/retinanet.py b/official/vision/beta/tasks/retinanet.py index d01a87037..b4387732f 100644 --- a/official/vision/beta/tasks/retinanet.py +++ b/official/vision/beta/tasks/retinanet.py @@ -218,11 +218,6 @@ class RetinaNetTask(base_task.Task): # Scales back gradient when LossScaleOptimizer is used. if isinstance(optimizer, tf.keras.mixed_precision.LossScaleOptimizer): grads = optimizer.get_unscaled_gradients(grads) - - # Apply gradient clipping. - if self.task_config.gradient_clip_norm > 0: - grads, _ = tf.clip_by_global_norm( - grads, self.task_config.gradient_clip_norm) optimizer.apply_gradients(list(zip(grads, tvars))) logs = {self.loss: loss} diff --git a/official/vision/beta/tasks/semantic_segmentation.py b/official/vision/beta/tasks/semantic_segmentation.py index aa14186b8..005c8759b 100644 --- a/official/vision/beta/tasks/semantic_segmentation.py +++ b/official/vision/beta/tasks/semantic_segmentation.py @@ -188,11 +188,6 @@ class SemanticSegmentationTask(base_task.Task): # used. if isinstance(optimizer, tf.keras.mixed_precision.LossScaleOptimizer): grads = optimizer.get_unscaled_gradients(grads) - - # Apply gradient clipping. - if self.task_config.gradient_clip_norm > 0: - grads, _ = tf.clip_by_global_norm( - grads, self.task_config.gradient_clip_norm) optimizer.apply_gradients(list(zip(grads, tvars))) logs = {self.loss: loss} diff --git a/official/vision/beta/tasks/video_classification.py b/official/vision/beta/tasks/video_classification.py index cc45efabe..321f5bc93 100644 --- a/official/vision/beta/tasks/video_classification.py +++ b/official/vision/beta/tasks/video_classification.py @@ -160,11 +160,6 @@ class VideoClassificationTask(base_task.Task): # used. if isinstance(optimizer, tf.keras.mixed_precision.LossScaleOptimizer): grads = optimizer.get_unscaled_gradients(grads) - - # Apply gradient clipping. - if self.task_config.gradient_clip_norm > 0: - grads, _ = tf.clip_by_global_norm( - grads, self.task_config.gradient_clip_norm) optimizer.apply_gradients(list(zip(grads, tvars))) logs = {self.loss: loss} -- GitLab