Merge branch 'main' into metal-bf16

huggingface · Jan 9, 2024 · b500aa7 · b500aa7
2 parents 9a48ae9 + 12b2a33
commit b500aa7
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diff --git a/Cargo.toml b/Cargo.toml
@@ -31,6 +31,14 @@ license = "MIT OR Apache-2.0"
 accelerate-src = { version = "0.3.2" }
 anyhow = { version = "1", features = ["backtrace"] }
 byteorder = "1.4.3"
+candle = { path = "./candle-core", package = "candle-core" }
+candle-datasets = { path = "./candle-datasets" }
+candle-flash-attn = { path = "./candle-flash-attn" }
+candle-kernels = { path = "./candle-kernels" }
+candle-metal-kernels = { path = "./candle-metal-kernels" }
+candle-nn = { path = "./candle-nn" }
+candle-onnx = { path = "./candle-onnx" }
+candle-transformers = { path = "./candle-transformers" }
 clap = { version = "4.2.4", features = ["derive"] }
 criterion = { version = "0.5.1", default-features=false }
 cudarc = { version = "0.9.14", features = ["f16"] }

diff --git a/README.md b/README.md
@@ -158,6 +158,7 @@ And then head over to
 - [`candle-ext`](https://github.com/mokeyish/candle-ext): An extension library to Candle that provides PyTorch functions not currently available in Candle.
 - [`kalosm`](https://github.com/floneum/floneum/tree/master/interfaces/kalosm): A multi-modal meta-framework in Rust for interfacing with local pre-trained models with support for controlled generation, custom samplers, in-memory vector databases, audio transcription, and more.
 - [`candle-sampling`](https://github.com/EricLBuehler/candle-sampling): Sampling techniques for Candle.
+- [`gpt-from-scratch-rs`](https://github.com/jeroenvlek/gpt-from-scratch-rs): A port of Andrej Karpathy's _Let's build GPT_ tutorial on YouTube showcasing the Candle API on a toy problem.
 
 If you have an addition to this list, please submit a pull request.
 

diff --git a/candle-book/Cargo.toml b/candle-book/Cargo.toml
@@ -11,11 +11,11 @@ readme = "README.md"
 
 [dependencies]
 accelerate-src = { workspace = true, optional = true }
-candle = { path = "../candle-core", version = "0.3.3", package = "candle-core" }
-candle-datasets = { path = "../candle-datasets", version = "0.3.3" }
-candle-nn = { path = "../candle-nn", version = "0.3.3" }
-candle-transformers = { path = "../candle-transformers", version = "0.3.3" }
-candle-flash-attn = { path = "../candle-flash-attn", version = "0.3.3", optional = true }
+candle = { workspace = true }
+candle-datasets = { workspace = true }
+candle-nn = { workspace = true }
+candle-transformers = { workspace = true }
+candle-flash-attn = { workspace = true, optional = true }
 safetensors = { workspace = true }
 serde = { workspace = true }
 serde_json = { workspace = true }

diff --git a/candle-core/Cargo.toml b/candle-core/Cargo.toml
@@ -12,9 +12,9 @@ readme = "README.md"
 [dependencies]
 accelerate-src = { workspace = true, optional = true }
 byteorder = { workspace = true }
-candle-kernels = { path = "../candle-kernels", version = "0.3.3", optional = true }
-candle-metal-kernels = { path = "../candle-metal-kernels", version = "0.3.3", optional = true }
-metal = { workspace = true, optional = true }
+candle-kernels = { workspace = true, optional = true }
+candle-metal-kernels = { workspace = true, optional = true }
+metal = { workspace = true, optional = true}
 cudarc = { workspace = true, optional = true }
 gemm = { workspace = true }
 half = { workspace = true }
@@ -48,4 +48,3 @@ metal = ["dep:metal", "dep:candle-metal-kernels"]
 [[bench]]
 name = "matmul"
 harness = false
-required-features = ["metal"]
diff --git a/candle-core/src/pickle.rs b/candle-core/src/pickle.rs
@@ -703,6 +703,7 @@ impl PthTensors {
     }
 
     pub fn get(&self, name: &str) -> Result<Option<Tensor>> {
+        use std::io::Read;
         let tensor_info = match self.tensor_infos.get(name) {
             None => return Ok(None),
             Some(tensor_info) => tensor_info,
@@ -712,14 +713,21 @@ impl PthTensors {
         let mut zip = zip::ZipArchive::new(zip_reader)?;
         let mut reader = zip.by_name(&tensor_info.path)?;
 
-        // Reading the data is a bit tricky as it can be strided, use an offset, etc.
-        // For now only support the basic case.
-        if tensor_info.layout.start_offset() != 0 || !tensor_info.layout.is_contiguous() {
+        // Reading the data is a bit tricky as it can be strided, for now only support the basic
+        // case.
+        if !tensor_info.layout.is_contiguous() {
             crate::bail!(
                 "cannot retrieve non-contiguous tensors {:?}",
                 tensor_info.layout
             )
         }
+        let start_offset = tensor_info.layout.start_offset();
+        if start_offset > 0 {
+            std::io::copy(
+                &mut reader.by_ref().take(start_offset as u64),
+                &mut std::io::sink(),
+            )?;
+        }
         let tensor = Tensor::from_reader(
             tensor_info.layout.shape().clone(),
             tensor_info.dtype,