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audiocraft/grids/audiogen/audiogen_base_16khz.py

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+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from ..musicgen._explorers import LMExplorer
+from ...environment import AudioCraftEnvironment
+
+
+@LMExplorer
+def explorer(launcher):
+    partitions = AudioCraftEnvironment.get_slurm_partitions(['team', 'global'])
+    launcher.slurm_(gpus=64, partition=partitions)
+    launcher.bind_(solver='audiogen/audiogen_base_16khz')
+    # replace this by the desired environmental sound dataset
+    launcher.bind_(dset='internal/sounds_16khz')
+
+    fsdp = {'autocast': False, 'fsdp.use': True}
+    medium = {'model/lm/model_scale': 'medium'}
+
+    launcher.bind_(fsdp)
+    launcher(medium)

audiocraft/grids/audiogen/audiogen_pretrained_16khz_eval.py

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+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+Evaluation with objective metrics for the pretrained AudioGen models.
+This grid takes signature from the training grid and runs evaluation-only stage.
+
+When running the grid for the first time, please use:
+REGEN=1 dora grid audiogen.audiogen_pretrained_16khz_eval
+and re-use the REGEN=1 option when the grid is changed to force regenerating it.
+
+Note that you need the proper metrics external libraries setup to use all
+the objective metrics activated in this grid. Refer to the README for more information.
+"""
+
+import os
+
+from ..musicgen._explorers import GenerationEvalExplorer
+from ...environment import AudioCraftEnvironment
+from ... import train
+
+
+def eval(launcher, batch_size: int = 32):
+    opts = {
+        'dset': 'audio/audiocaps_16khz',
+        'solver/audiogen/evaluation': 'objective_eval',
+        'execute_only': 'evaluate',
+        '+dataset.evaluate.batch_size': batch_size,
+        '+metrics.fad.tf.batch_size': 32,
+    }
+    # binary for FAD computation: replace this path with your own path
+    metrics_opts = {
+        'metrics.fad.tf.bin': '/data/home/jadecopet/local/usr/opt/google-research'
+    }
+    opt1 = {'generate.lm.use_sampling': True, 'generate.lm.top_k': 250, 'generate.lm.top_p': 0.}
+    opt2 = {'transformer_lm.two_step_cfg': True}
+
+    sub = launcher.bind(opts)
+    sub.bind_(metrics_opts)
+
+    # base objective metrics
+    sub(opt1, opt2)
+
+
+@GenerationEvalExplorer
+def explorer(launcher):
+    partitions = AudioCraftEnvironment.get_slurm_partitions(['team', 'global'])
+    launcher.slurm_(gpus=4, partition=partitions)
+
+    if 'REGEN' not in os.environ:
+        folder = train.main.dora.dir / 'grids' / __name__.split('.', 2)[-1]
+        with launcher.job_array():
+            for sig in folder.iterdir():
+                if not sig.is_symlink():
+                    continue
+                xp = train.main.get_xp_from_sig(sig.name)
+                launcher(xp.argv)
+        return
+
+    audiogen_base = launcher.bind(solver="audiogen/audiogen_base_16khz")
+    audiogen_base.bind_({'autocast': False, 'fsdp.use': True})
+
+    audiogen_base_medium = audiogen_base.bind({'continue_from': '//pretrained/facebook/audiogen-medium'})
+    audiogen_base_medium.bind_({'model/lm/model_scale': 'medium'})
+    eval(audiogen_base_medium, batch_size=128)