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2 Commits
acbccebb2c
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9af36e7145
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| 9af36e7145 | |||
| 23fddbe5b9 |
@@ -14,7 +14,7 @@ class NumberEmbedder(nn.Module):
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def forward(self, x):
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def forward(self, x):
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return self.net(x)
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return self.net(x)
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# 3) Comparator head: takes (ea, eb, e) -> logit for "a > b"
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# MLP Comparator head: takes (ea, eb, e) -> logit for "a > b"
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class PairwiseComparator(nn.Module):
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class PairwiseComparator(nn.Module):
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def __init__(self, d=2, hidden=4, k=0.5):
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def __init__(self, d=2, hidden=4, k=0.5):
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super().__init__()
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super().__init__()
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@@ -163,7 +163,7 @@ def training_entry():
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with lzma.open(TRAINING_LOG_PATH, mode='wt') as tlog:
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with lzma.open(TRAINING_LOG_PATH, mode='wt') as tlog:
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# training loop
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# training loop
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training_start_time = datetime.datetime.now()
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training_start_time = datetime.datetime.now()
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last_ack = datetime.datetime.now(datetime.timezone.utc)
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last_ack = datetime.datetime.now()
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for step in range(TRAIN_STEPS):
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for step in range(TRAIN_STEPS):
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a, b, y = sample_batch(TRAIN_BATCHSZ)
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a, b, y = sample_batch(TRAIN_BATCHSZ)
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@@ -184,7 +184,7 @@ def training_entry():
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# also print to normal text log occasionally to show some activity.
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# also print to normal text log occasionally to show some activity.
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# every 10 steps check if its been longer than 5 seconds since we've updated the user
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# every 10 steps check if its been longer than 5 seconds since we've updated the user
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if step % 10 == 0:
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if step % 10 == 0:
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if (datetime.datetime.now(datetime.timezone.utc) - last_ack).total_seconds() > 5:
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if (datetime.datetime.now() - last_ack).total_seconds() > 5:
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log.info(f"still training... step={step} of {TRAIN_STEPS}")
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log.info(f"still training... step={step} of {TRAIN_STEPS}")
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last_ack = datetime.datetime.now()
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last_ack = datetime.datetime.now()
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