From e2f72fe52f3a4fce6578a9641cadcd503d20d99b Mon Sep 17 00:00:00 2001
From: Daniel Han-Chen <danielhanchen@gmail.com>
Date: Thu, 1 Feb 2024 03:04:46 +1100
Subject: [PATCH] Revert

---
 unsloth/models/llama.py  | 17 ++++++++---------
 unsloth/models/mapper.py |  1 -
 2 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 3f1bd24b0c..e39649646b 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -232,9 +232,9 @@ def LlamaAttention_fast_forward_inference(
     head_dim   = self.head_dim
     assert(n_kv_heads * n_groups == n_heads)
 
-    Qn = fast_linear_forward(self.q_proj, Xn)
-    Kn = fast_linear_forward(self.k_proj, Xn)
-    Vn = fast_linear_forward(self.v_proj, Xn)
+    Qn = self.q_proj(Xn)
+    Kn = self.k_proj(Xn)
+    Vn = self.v_proj(Xn)
     Qn = Qn.view(bsz, 1, n_heads,    head_dim).transpose(1, 2)
     Kn = Kn.view(bsz, 1, n_kv_heads, head_dim).transpose(1, 2)
     Vn = Vn.view(bsz, 1, n_kv_heads, head_dim).transpose(1, 2)
@@ -260,22 +260,21 @@ def LlamaAttention_fast_forward_inference(
     # Attention
     A = torch.matmul(Qn, Knn.transpose(2, 3))
     A *= 1.0 / math_sqrt(self.head_dim)
-    A[:] = torch.nn.functional.softmax(A, dim = -1, dtype = torch.float32)#.to(A.dtype)
-    A = torch.matmul(A, Vnn, out = Qn)
+    A = torch.nn.functional.softmax(A, dim = -1, dtype = torch.float32).to(A.dtype)
+    A = torch.matmul(A, Vnn)
     A = A.transpose(1, 2)
     A = A.reshape(bsz, 1, self.hidden_size)
-    A = fast_linear_forward(self.o_proj, A)
+    A = self.o_proj(A)
     return A, (Kn, Vn)
 pass
 
 
-torch_silu = torch.nn.functional.silu
 def fast_mlp_inference(self, X):
     # gate = self.gate_proj(X)
     # up   = self.up_proj(X)
     gate = fast_linear_forward(self.gate_proj, X)
     up   = fast_linear_forward(self.  up_proj, X)
-    gate = torch_silu(gate, inplace = True)
+    gate = torch.nn.functional.silu(gate, inplace = True)
     gate *= up
 
     # X = self.down_proj(gate)
@@ -725,7 +724,7 @@ def LlamaForCausalLM_fast_forward(
 
     hidden_states = outputs[0]
     bsz, q_len, hd = hidden_states.shape
-    if bsz == 1 and q_len == 1:
+    if False:#bsz == 1 and q_len == 1:
         logits = torch.mv(self.lm_head.weight, hidden_states.ravel())
         logits = logits.unsqueeze(0).unsqueeze(0)
     else:
diff --git a/unsloth/models/mapper.py b/unsloth/models/mapper.py
index a5509cdb25..c8c73dce10 100644
--- a/unsloth/models/mapper.py
+++ b/unsloth/models/mapper.py
@@ -68,7 +68,6 @@ __INT_TO_FLOAT_MAPPER = \
         "01-ai/Yi-6B",
     ),
     "unsloth/solar-10.7b-bnb-4bit" : (
-        "unsloth/solar-10.7b",
         "upstage/SOLAR-10.7B-v1.0",
     ),
 }