[Misc] Remove Mixtral device="cuda" declarations (#4543)
Remove the device="cuda" declarations in mixtral as promised in #4343
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@ -96,13 +96,11 @@ class MixtralMoE(nn.Module):
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torch.empty(self.num_total_experts,
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2 * self.intermediate_size,
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self.hidden_size,
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device="cuda",
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dtype=self.params_dtype))
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self.w2s = nn.Parameter(
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torch.empty(self.num_total_experts,
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self.hidden_size,
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self.intermediate_size,
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device="cuda",
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dtype=self.params_dtype))
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set_weight_attrs(self.ws, {
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@ -114,22 +112,20 @@ class MixtralMoE(nn.Module):
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# Scaling factors for FP8 weights
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self.ws_scale = nn.Parameter(
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torch.ones(
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self.num_total_experts, device="cuda", dtype=torch.float32),
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torch.ones(self.num_total_experts, dtype=torch.float32),
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requires_grad=False) if self.use_fp8 else None
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self.w2s_scale = nn.Parameter(
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torch.ones(
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self.num_total_experts, device="cuda", dtype=torch.float32),
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torch.ones(self.num_total_experts, dtype=torch.float32),
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requires_grad=False) if self.use_fp8 else None
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# Scaling factors for FP8 activations
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need_act_scales = (self.use_fp8
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and quant_config.activation_scheme == "static")
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self.as_scale = nn.Parameter(
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torch.zeros(1, device="cuda", dtype=torch.float32),
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torch.zeros(1, dtype=torch.float32),
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requires_grad=False) if need_act_scales else None
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self.a2s_scale = nn.Parameter(
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torch.zeros(1, device="cuda", dtype=torch.float32),
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torch.zeros(1, dtype=torch.float32),
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requires_grad=False) if need_act_scales else None
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if need_act_scales:
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