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Reduce debug freq
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@ -592,7 +592,7 @@ param_rms_smooth1: Smoothing proportion for parameter matrix, if assumed rank of
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# (where the stats permit).
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scale = (S.clamp(min=eps) / cur_param_var.clamp(min=eps)).sqrt()
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if random.random() < 0.01:
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if random.random() < 0.001:
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logging.info(f"shape={p.shape}, dim={dim}, scale={scale[0].flatten()[::10]}, cur_param_var={cur_param_var[0].flatten()[::10]}, S={S[0].flatten()[::10]}")
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# scale shape: (batch_size, 1, size, 1, 1)
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@ -619,7 +619,7 @@ param_rms_smooth1: Smoothing proportion for parameter matrix, if assumed rank of
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# cur_scales for the other dims.
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cur_scales = [None] * ndim
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debug = True #(random.random() < 0.001)
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debug = (random.random() < 0.001)
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for i in range(4): # for 4 iterations (this is quite arbitrary)
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for dim in range(1, ndim):
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size = p.shape[dim]
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