facebookresearch--audiocraft
Jade Clara Copet
67 行
2.0 KiB
Python
67 行
2.0 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the license found in the
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# LICENSE file in the root directory of this source tree.
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import treetable as tt
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from .._base_explorers import BaseExplorer
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class DiffusionExplorer(BaseExplorer):
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eval_metrics = ["sisnr", "visqol"]
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def stages(self):
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return ["train", "valid", "valid_ema", "evaluate", "evaluate_ema"]
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def get_grid_meta(self):
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"""Returns the list of Meta information to display for each XP/job.
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"""
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return [
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tt.leaf("index", align=">"),
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tt.leaf("name", wrap=140),
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tt.leaf("state"),
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tt.leaf("sig", align=">"),
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]
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def get_grid_metrics(self):
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"""Return the metrics that should be displayed in the tracking table.
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"""
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return [
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tt.group(
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"train",
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[
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tt.leaf("epoch"),
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tt.leaf("loss", ".3%"),
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],
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align=">",
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),
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tt.group(
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"valid",
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[
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tt.leaf("loss", ".3%"),
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# tt.leaf("loss_0", ".3%"),
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],
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align=">",
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),
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tt.group(
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"valid_ema",
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[
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tt.leaf("loss", ".3%"),
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# tt.leaf("loss_0", ".3%"),
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],
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align=">",
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),
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tt.group(
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"evaluate", [tt.leaf("rvm", ".4f"), tt.leaf("rvm_0", ".4f"),
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tt.leaf("rvm_1", ".4f"), tt.leaf("rvm_2", ".4f"),
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tt.leaf("rvm_3", ".4f"), ], align=">"
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),
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tt.group(
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"evaluate_ema", [tt.leaf("rvm", ".4f"), tt.leaf("rvm_0", ".4f"),
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tt.leaf("rvm_1", ".4f"), tt.leaf("rvm_2", ".4f"),
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tt.leaf("rvm_3", ".4f")], align=">"
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),
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]
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