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making unconditional generation work

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The unconditional generation works now but if the seed is fixed, the sample is the same every time.
n_samples > 1 will give different samples though.
I am giving the start token as '<|endoftext|>' for the unconditional generation.
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dhanajitb 2019-03-28 22:46:15 +05:30 committed by GitHub
parent 694e2117f3
commit f872eb98c2
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examples/run_gpt2.py
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@ -106,6 +106,23 @@ def run_model():
print("=" * 40 + " SAMPLE " + str(generated) + " " + "=" * 40)
print(text)
print("=" * 80)
if args.unconditional:
generated = 0
for _ in range(args.nsamples // args.batch_size):
out = sample_sequence(
model=model, length=args.length,
context=None,
start_token=enc.encoder['<|endoftext|>'],
batch_size=args.batch_size,
temperature=args.temperature, top_k=args.top_k, device=device
)
out = out[:,1:].tolist()
for i in range(args.batch_size):
generated += 1
text = enc.decode(out[i])
print("=" * 40 + " SAMPLE " + str(generated) + " " + "=" * 40)
print(text)
print("=" * 80)
if __name__ == '__main__':
run_model()