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add Falcon 40B model support #368

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LLukas22 merged 13 commits into from
Jul 27, 2023
Merged

add Falcon 40B model support #368

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dadb104
add Falcon 40B model support
skirodev Jul 15, 2023
e28e0ef
disable falcon by default
skirodev Jul 15, 2023
5b757aa
fix formatting
skirodev Jul 15, 2023
334e8be
remove needless borrow
skirodev Jul 15, 2023
5c40a19
fix bot token id
skirodev Jul 16, 2023
71c3273
disable falcon by default
skirodev Jul 16, 2023
565ca6d
fix attention_norm weight error
skirodev Jul 16, 2023
9ae6e56
Merge branch 'rustformers:main' into feat/falcon
skirodev Jul 17, 2023
a804a5f
fix bigv
skirodev Jul 17, 2023
191ec02
fix formatting
skirodev Jul 17, 2023
bce0b9a
Merge branch 'rustformers:main' into feat/falcon
skirodev Jul 17, 2023
871a5d8
Merge branch 'rustformers:main' into feat/falcon
skirodev Jul 26, 2023
0afd18e
remove bos token id and use float16 kv memory type
skirodev Jul 26, 2023
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14 changes: 14 additions & 0 deletions crates/ggml/src/context.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -561,6 +561,20 @@ impl Context {
let tensor = unsafe { sys::ggml_gelu(self.as_ptr(), a.ptr.as_ptr()) };
self.new_tensor_raw(tensor)
}

/// flash attention.
pub fn op_flash_attn(&self, q: &Tensor, k: &Tensor, v: &Tensor, masked: bool) -> Tensor {
let tensor = unsafe {
sys::ggml_flash_attn(
self.as_ptr(),
q.ptr.as_ptr(),
k.ptr.as_ptr(),
v.ptr.as_ptr(),
masked,
)
};
self.new_tensor_raw(tensor)
}
}
// Public to this crate methods
impl Context {
Expand Down
110 changes: 75 additions & 35 deletions crates/models/falcon/src/lib.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -63,10 +63,29 @@ impl KnownModel for Falcon {
let lm_head = tl.load("lm_head.weight")?;

let mut layers = Vec::new();
// utilizing n_head_kv to determine the model version (parameters)
let Hyperparameters { n_head_kv, .. } = hyperparameters;
for i in 0..hyperparameters.n_layer {
let (input_layernorm_name, attention_norm_name) = if n_head_kv == 1 {
// falcon 7b
(format!("transformer.h.{i}.input_layernorm"), None)
} else {
// falcon 40b
(
format!("transformer.h.{i}.ln_mlp"),
Some(format!("transformer.h.{i}.ln_attn")),
)
};
let layer = Layer {
attention_norm: tl.load(&format!("transformer.h.{i}.input_layernorm.weight"))?,
attention_norm_b: tl.load(&format!("transformer.h.{i}.input_layernorm.bias"))?,
input_layernorm: tl.load(&format!("{}.weight", input_layernorm_name))?,
input_layernorm_b: tl.load(&format!("{}.bias", input_layernorm_name))?,
attention_norm: attention_norm_name
.as_ref()
.map(|path| tl.load(&format!("{}.weight", path)))
.transpose()?,
attention_norm_b: attention_norm_name
.map(|path| tl.load(&format!("{}.bias", path)))
.transpose()?,

query_key_value: tl.load(&format!(
"transformer.h.{i}.self_attention.query_key_value.weight"
Expand Down Expand Up @@ -118,6 +137,7 @@ impl KnownModel for Falcon {
let Hyperparameters {
n_embd,
n_head,
n_head_kv,
n_vocab,
n_layer,
..
Expand All @@ -130,12 +150,6 @@ impl KnownModel for Falcon {
let ctx0 = builder.ctx0.borrow();
let embd = builder.embd;
let mut input_layer = ctx0.op_get_rows(&self.tok_embeddings, embd);
let repeat_dummy = ctx0.new_tensor_3d(
input_layer.get_type(),
head_dim,
input_len + session_len,
n_head,
);

let f32_size = std::mem::size_of::<f32>();

Expand All @@ -155,21 +169,40 @@ impl KnownModel for Falcon {
ctx0.use_scratch(builder.get_scratch(0));

// self-attention
current = ctx0.op_norm(&input_layer);
current = ctx0.op_add(
layernorm_output = ctx0.op_norm(&input_layer);
layernorm_output = ctx0.op_add(
&ctx0.op_mul(
&ctx0.op_repeat(&self.layers[il].attention_norm, &current),
&current,
&ctx0.op_repeat(&self.layers[il].input_layernorm, &layernorm_output),
&layernorm_output,
),
&ctx0.op_repeat(&self.layers[il].attention_norm_b, &current),
&ctx0.op_repeat(&self.layers[il].input_layernorm_b, &layernorm_output),
);

layernorm_output = current.share();
if n_head_kv == 1 {
// Falcon-7B only
current = layernorm_output.share();
} else {
// Falcon-40B only
current = ctx0.op_norm(&input_layer);
current = ctx0.op_add(
&ctx0.op_mul(
&ctx0.op_repeat(
self.layers[il].attention_norm.as_ref().unwrap(),
&current,
),
&current,
),
&ctx0.op_repeat(
self.layers[il].attention_norm_b.as_ref().unwrap(),
&current,
),
);
}

// compute QKV
current = ctx0.op_mul_mat(&self.layers[il].query_key_value, &current);

let fused_qkv_row_nb = (n_embd + 2 * (n_embd / n_head)) * f32_size;
let fused_qkv_row_nb = head_dim * (n_head + 2 * n_head_kv) * f32_size;
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Resolved

let mut qcur = ctx0.op_view_3d(
&current,
Expand All @@ -180,16 +213,16 @@ impl KnownModel for Falcon {

let mut kcur = ctx0.op_view_3d(
&current,
(head_dim, 1, n),
(head_dim, n_head_kv, n),
(head_dim * f32_size, fused_qkv_row_nb),
n_embd * f32_size,
head_dim * n_head * f32_size,
);

let vcur = ctx0.op_view_3d(
&current,
(head_dim, 1, n),
(head_dim, n_head_kv, n),
(head_dim * f32_size, fused_qkv_row_nb),
(n_embd + head_dim) * f32_size,
head_dim * (n_head + n_head_kv) * f32_size,
);

// using mode = 2 for neox mode
Expand All @@ -200,13 +233,13 @@ impl KnownModel for Falcon {

let k = ctx0.op_view_1d(
memory_k,
n * head_dim,
(memory_k_size * head_dim) * (il * ctx_size + session_len),
n * n_head_kv * head_dim,
(memory_k_size * n_head_kv * head_dim) * (il * ctx_size + session_len),
);
let v = ctx0.op_view_1d(
memory_v,
n * head_dim,
(memory_v_size * head_dim) * (il * ctx_size + session_len),
n * n_head_kv * head_dim,
(memory_v_size * n_head_kv * head_dim) * (il * ctx_size + session_len),
);

gf.build_forward_expand(&ctx0.op_cpy(&kcur, &k));
Expand All @@ -215,21 +248,21 @@ impl KnownModel for Falcon {
// Q = Qcur.contiguous().view(n_embd/n_head, n_head, N).permute(0, 2, 1, 3)
let bigq = ctx0.op_permute(&qcur, (0, 2, 1, 3));

let mut bigk = ctx0.op_permute(
let bigk = ctx0.op_permute(
&ctx0.op_reshape_3d(
&ctx0.op_view_1d(
memory_k,
(session_len + n) * head_dim,
il * ctx_size * memory_k_size * head_dim,
(session_len + n) * n_head_kv * head_dim,
il * ctx_size * memory_k_size * n_head_kv * head_dim,
),
head_dim,
1,
n_head_kv,
session_len + n,
),
(0, 2, 1, 3),
);

// K * Q
bigk = ctx0.op_cont(&ctx0.op_repeat(&bigk, &repeat_dummy));
let big_kq = ctx0.op_mul_mat(&bigk, &bigq);

// KQ_scaled = KQ / sqrt(n_embd/n_head)
Expand All @@ -246,18 +279,17 @@ impl KnownModel for Falcon {
&ctx0.op_reshape_3d(
&ctx0.op_view_1d(
memory_v,
(session_len + n) * head_dim,
il * ctx_size * memory_v_size * head_dim,
(session_len + n) * n_head_kv * head_dim,
il * ctx_size * memory_v_size * n_head_kv * head_dim,
),
head_dim,
1,
n_head_kv,
session_len + n,
),
(0, 2, 1, 3),
);
bigv = ctx0.op_cont(&ctx0.op_transpose(&ctx0.op_repeat(&bigv, &repeat_dummy)));
bigv = ctx0.op_cont(&ctx0.op_transpose(&bigv));

// KQV = transpose(V) * KQ_soft_max
let big_kqv = ctx0.op_mul_mat(&bigv, &big_kq_softmax);
// KQV_merged = KQV.permute(0, 2, 1, 3)
let big_kqv_merged = ctx0.op_permute(&big_kqv, (0, 2, 1, 3));
Expand Down Expand Up @@ -361,6 +393,8 @@ pub struct Hyperparameters {
n_embd: usize,
/// n_heads
n_head: usize,
// Number of heads for key-value pairs
n_head_kv: usize,
/// Number of layers in the model
n_layer: usize,
/// file_type
Expand All @@ -373,6 +407,7 @@ impl llm_base::Hyperparameters for Hyperparameters {
n_vocab: util::read_i32(reader)?.try_into()?,
n_embd: util::read_i32(reader)?.try_into()?,
n_head: util::read_i32(reader)?.try_into()?,
n_head_kv: util::read_i32(reader)?.try_into()?,
n_layer: util::read_i32(reader)?.try_into()?,
file_type: util::read_filetype(reader)?,
};
Expand All @@ -384,6 +419,7 @@ impl llm_base::Hyperparameters for Hyperparameters {
util::write_i32(writer, self.n_vocab.try_into()?)?;
util::write_i32(writer, self.n_embd.try_into()?)?;
util::write_i32(writer, self.n_head.try_into()?)?;
util::write_i32(writer, self.n_head_kv.try_into()?)?;
util::write_i32(writer, self.n_layer.try_into()?)?;
util::write_i32(writer, self.file_type.into())?;
Ok(())
Expand All @@ -404,8 +440,12 @@ impl llm_base::Hyperparameters for Hyperparameters {

struct Layer {
// normalization
attention_norm: Tensor,
attention_norm_b: Tensor,
input_layernorm: Tensor,
input_layernorm_b: Tensor,

// Falcon-40B only
attention_norm: Option<Tensor>,
attention_norm_b: Option<Tensor>,

// attention
query_key_value: Tensor,
Expand Down