Adds yaml file for training on k600.

PiperOrigin-RevId: 376094072

official/vision/beta/configs/experiments/video_classification/k600_3d-resnet50g_tpu.yaml

+# 3D ResNet-50g video classification on Kinetics-600.
+#
+# --experiment_type=video_classification_kinetics600
+# Expected accuracy: 78.7% accuracy, 93.6% top-5.
+# Train on TPU: v3-128, eval on TPU: v3-32
+runtime:
+  distribution_strategy: 'tpu'
+  mixed_precision_dtype: 'bfloat16'
+task:
+  init_checkpoint: null
+  init_checkpoint_modules: all
+  losses:
+    l2_weight_decay: 0.0001
+    label_smoothing: 0.0
+  model:
+    aggregate_endpoints: false
+    backbone:
+      resnet_3d:
+        block_specs: !!python/tuple
+        - temporal_kernel_sizes: !!python/tuple
+          - 3
+          - 3
+          - 3
+          temporal_strides: 1
+          use_self_gating: true
+        - temporal_kernel_sizes: !!python/tuple
+          - 3
+          - 1
+          - 3
+          - 1
+          temporal_strides: 1
+          use_self_gating: true
+        - temporal_kernel_sizes: !!python/tuple
+          - 3
+          - 1
+          - 3
+          - 1
+          - 3
+          - 1
+          temporal_strides: 1
+          use_self_gating: true
+        - temporal_kernel_sizes: !!python/tuple
+          - 1
+          - 3
+          - 1
+          temporal_strides: 1
+          use_self_gating: true
+        model_id: 50
+        stem_conv_temporal_kernel_size: 5
+        stem_conv_temporal_stride: 2
+        stem_pool_temporal_stride: 2
+        stem_type: v0
+        stochastic_depth_drop_rate: 0.0
+      type: resnet_3d
+    dropout_rate: 0.2
+    model_type: video_classification
+    norm_activation:
+      activation: relu
+      norm_epsilon: 1.0e-05
+      norm_momentum: 0.9
+      use_sync_bn: false
+  train_data:
+    aug_max_area_ratio: 1.0
+    aug_max_aspect_ratio: 2.0
+    aug_min_area_ratio: 0.49
+    aug_min_aspect_ratio: 0.5
+    drop_remainder: true
+    dtype: 'bfloat16'
+    feature_shape: !!python/tuple
+    - 64
+    - 224
+    - 224
+    - 3
+    global_batch_size: 1024
+    min_image_size: 256
+    name: kinetics600
+    num_classes: 600
+    split: train
+  validation_data:
+    dtype: 'bfloat16'
+    feature_shape: !!python/tuple
+    - 250
+    - 224
+    - 224
+    - 3
+    global_batch_size: 64
+    min_image_size: 256
+    name: kinetics600
+    num_classes: 600
+    num_examples: 27780
+    num_test_clips: 1
+    num_test_crops: 1
+    one_hot: true
+trainer:
+  optimizer_config:
+    learning_rate:
+      cosine:
+        alpha: 0.0
+        decay_steps: 71400
+        initial_learning_rate: 1.6
+        name: CosineDecay
+      type: cosine
+    warmup:
+      linear:
+        name: linear
+        warmup_learning_rate: 0
+        warmup_steps: 1785
+      type: linear
+  train_steps: 71400
+  steps_per_loop: 500
+  summary_interval: 500
+  validation_interval: 500