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-rw-r--r--CHANGELOG.md2
-rw-r--r--Cargo.toml2
-rw-r--r--candle-book/Cargo.toml10
-rw-r--r--candle-core/Cargo.toml2
-rw-r--r--candle-core/src/tensor.rs65
-rw-r--r--candle-datasets/Cargo.toml4
-rw-r--r--candle-examples/Cargo.toml10
-rw-r--r--candle-examples/examples/mnist-training/main.rs2
-rw-r--r--candle-flash-attn/Cargo.toml6
-rw-r--r--candle-kernels/Cargo.toml2
-rw-r--r--candle-nn/Cargo.toml2
-rw-r--r--candle-pyo3/Cargo.toml2
-rw-r--r--candle-transformers/Cargo.toml4
-rw-r--r--candle-wasm-examples/llama2-c/Cargo.toml4
-rw-r--r--candle-wasm-examples/whisper/Cargo.toml4
-rw-r--r--candle-wasm-examples/yolo/Cargo.toml4
16 files changed, 95 insertions, 30 deletions
diff --git a/CHANGELOG.md b/CHANGELOG.md
index d6394549..a52429cf 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,7 +1,7 @@
# Changelog
This documents the main changes to the `candle` crate.
-## Unreleased
+## v0.2.1 - Unreleased
### Added
diff --git a/Cargo.toml b/Cargo.toml
index dc48ccd8..ce41876a 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -18,7 +18,7 @@ exclude = [
resolver = "2"
[workspace.package]
-version = "0.2.0"
+version = "0.2.1"
edition = "2021"
description = "Minimalist ML framework."
repository = "https://github.com/huggingface/candle"
diff --git a/candle-book/Cargo.toml b/candle-book/Cargo.toml
index 6cd0a487..320fb887 100644
--- 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 = "0.2.0", package = "candle-core" }
-candle-datasets = { path = "../candle-datasets", version = "0.2.0" }
-candle-nn = { path = "../candle-nn", version = "0.2.0" }
-candle-transformers = { path = "../candle-transformers", version = "0.2.0" }
-candle-flash-attn = { path = "../candle-flash-attn", version = "0.2.0", optional = true }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
+candle-datasets = { path = "../candle-datasets", version = "0.2.1" }
+candle-nn = { path = "../candle-nn", version = "0.2.1" }
+candle-transformers = { path = "../candle-transformers", version = "0.2.1" }
+candle-flash-attn = { path = "../candle-flash-attn", version = "0.2.1", optional = true }
safetensors = { workspace = true }
serde = { workspace = true }
serde_json = { workspace = true }
diff --git a/candle-core/Cargo.toml b/candle-core/Cargo.toml
index 698cdae0..e7213919 100644
--- a/candle-core/Cargo.toml
+++ b/candle-core/Cargo.toml
@@ -12,7 +12,7 @@ readme = "README.md"
[dependencies]
accelerate-src = { workspace = true, optional = true }
byteorder = { workspace = true }
-candle-kernels = { path = "../candle-kernels", version = "0.2.0", optional = true }
+candle-kernels = { path = "../candle-kernels", version = "0.2.1", optional = true }
cudarc = { workspace = true, optional = true }
gemm = { workspace = true }
half = { workspace = true }
diff --git a/candle-core/src/tensor.rs b/candle-core/src/tensor.rs
index 12e98029..ec89af12 100644
--- a/candle-core/src/tensor.rs
+++ b/candle-core/src/tensor.rs
@@ -730,18 +730,24 @@ impl Tensor {
self.sum_impl(mean_dims, false)? * scale
}
+ /// Gathers the maximum value across the selected dimension. The resulting shape has the same
+ /// number of dimensions as the original tensor and the select dimension has a single element.
pub fn max_keepdim<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, true, ReduceOp::Max)
}
+ /// Similar to `max_keepdim` but the target dimension is squeezed.
pub fn max<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, false, ReduceOp::Max)
}
+ /// Gathers the minimum value across the selected dimension. The resulting shape has the same
+ /// number of dimensions as the original tensor and the select dimension has a single element.
pub fn min_keepdim<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, true, ReduceOp::Min)
}
+ /// Similar to `min_keepdim` but the target dimension is squeezed.
pub fn min<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, false, ReduceOp::Min)
}
@@ -750,6 +756,7 @@ impl Tensor {
self.reduce_impl(dim, true, ReduceOp::ArgMax)
}
+ /// Similar to `argmax_keepdim` but the target dimension is squeezed.
pub fn argmax<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, false, ReduceOp::ArgMax)
}
@@ -758,10 +765,15 @@ impl Tensor {
self.reduce_impl(dim, true, ReduceOp::ArgMin)
}
+ /// Similar to `argmin_keepdim` but the target dimension is squeezed.
pub fn argmin<D: Dim>(&self, dim: D) -> Result<Self> {
self.reduce_impl(dim, false, ReduceOp::ArgMin)
}
+ /// Element-wise comparison between two tensors, e.g. equality, greater than, ... The actual
+ /// comparison operation is specified by the `op` argument.
+ ///
+ /// The returned tensor has the same shape as the original tensors and uses `u8` elements.
pub fn cmp(&self, rhs: &Self, op: CmpOp) -> Result<Self> {
let shape = self.same_shape_binary_op(rhs, "cmp")?;
let storage = self
@@ -771,30 +783,45 @@ impl Tensor {
Ok(from_storage(storage, shape.dims(), op, false))
}
+ /// Element-wise equality.
pub fn eq(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Eq)
}
+ /// Element-wise non-equality.
pub fn ne(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Ne)
}
+ /// Element-wise comparison with lower-than, the returned tensor uses value 1 where `self <
+ /// rhs` and 0 otherwise.
pub fn lt(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Lt)
}
+ /// Element-wise comparison with greater-than, the returned tensor uses value 1 where `self >
+ /// rhs` and 0 otherwise.
pub fn gt(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Gt)
}
+ /// Element-wise comparison with greater-equal, the returned tensor uses value 1 where `self >=
+ /// rhs` and 0 otherwise.
pub fn ge(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Ge)
}
+ /// Element-wise comparison with lower-equal, the returned tensor uses value 1 where `self <=
+ /// rhs` and 0 otherwise.
pub fn le(&self, rhs: &Self) -> Result<Self> {
self.cmp(rhs, CmpOp::Le)
}
+ /// Upsample the input tensor to the `(target_h, target_w)` size, taking the value of the
+ /// nearest element.
+ ///
+ /// The input tensor should have four dimensions, `(batch, channels, h, w)`, the returned
+ /// tensor also has four dimensions, `(batch, channels, target_h, target_w)`.
pub fn upsample_nearest2d(&self, target_h: usize, target_w: usize) -> Result<Self> {
let (n, c, _h, _w) = self.dims4()?;
let op = BackpropOp::new1(self, Op::UpsampleNearest2D);
@@ -804,11 +831,19 @@ impl Tensor {
Ok(from_storage(storage, (n, c, target_h, target_w), op, false))
}
+ /// 2D average pooling over an input tensor with multiple channels.
+ ///
+ /// The input tensor should have four dimensions, `(batch, channels, h, w)`, the returned
+ /// tensor also has four dimensions, `(batch, channels, h', w')`. The pooling is performed on
+ /// the two last dimensions using a kernel of size `sz`. The returned element is the average
+ /// value over the kernel window.
pub fn avg_pool2d<T: crate::ToUsize2>(&self, sz: T) -> Result<Self> {
let sz = sz.to_usize2();
self.avg_pool2d_with_stride(sz, sz)
}
+ /// Same as `avg_pool2d` but with a `stride` that can be set to a value different from the
+ /// kernel size.
pub fn avg_pool2d_with_stride<T: crate::ToUsize2>(
&self,
kernel_size: T,
@@ -831,11 +866,19 @@ impl Tensor {
Ok(from_storage(storage, (n, c, h_out, w_out), op, false))
}
+ /// 2D max pooling over an input tensor with multiple channels.
+ ///
+ /// The input tensor should have four dimensions, `(batch, channels, h, w)`, the returned
+ /// tensor also has four dimensions, `(batch, channels, h', w')`. The pooling is performed on
+ /// the two last dimensions using a kernel of size `sz`, the returned element is the maximum
+ /// value over the kernel window.
pub fn max_pool2d<T: crate::ToUsize2>(&self, sz: T) -> Result<Self> {
let sz = sz.to_usize2();
self.max_pool2d_with_stride(sz, sz)
}
+ /// Same as `max_pool2d` but with a `stride` that can be set to a value different from the
+ /// kernel size.
pub fn max_pool2d_with_stride<T: crate::ToUsize2>(
&self,
kernel_size: T,
@@ -1022,6 +1065,7 @@ impl Tensor {
Ok(from_storage(storage, self.shape(), op, false))
}
+ /// Accumulate element from `source` at indexes `indexes` and add them to `self`.
pub fn index_add<D: Dim>(&self, indexes: &Self, source: &Self, dim: D) -> Result<Self> {
let dim = dim.to_index(self.shape(), "index-add")?;
let source_dims = source.dims();
@@ -1070,6 +1114,17 @@ impl Tensor {
Ok(from_storage(storage, self.shape(), op, false))
}
+ /// Gather values across the target dimension.
+ ///
+ /// # Arguments
+ ///
+ /// * `self` - The input tensor.
+ /// * `indexes` - The indices of elements to gather, this should have the same shape as `self`
+ /// but can have a different number of elements on the target dimension.
+ /// * `dim` - the target dimension.
+ ///
+ /// The resulting tensor has the same shape as `indexes` and use values from `self` indexed on
+ /// dimension `dim` by the values in `indexes`.
pub fn gather<D: Dim>(&self, indexes: &Self, dim: D) -> Result<Self> {
let dim = dim.to_index(self.shape(), "gather")?;
let self_dims = self.dims();
@@ -1100,6 +1155,13 @@ impl Tensor {
Ok(from_storage(storage, indexes.shape(), op, false))
}
+ /// Select values for the input tensor at the target indexes across the specified dimension.
+ ///
+ /// The `indexes` is argument is an int tensor with a single dimension.
+ /// The output has the same number of dimension as the `self` input. The target dimension of
+ /// the output has length the length of `indexes` and the values are taken from `self` using
+ /// the index from `indexes`. Other dimensions have the same number of elements as the input
+ /// tensor.
pub fn index_select<D: Dim>(&self, indexes: &Self, dim: D) -> Result<Self> {
let dim = dim.to_index(self.shape(), "index-select")?;
let indexes_len = match indexes.dims() {
@@ -1858,6 +1920,8 @@ impl Tensor {
Ok(from_storage(storage, shape, op, false))
}
+ /// Pad the input tensor using 0s along dimension `dim`. This adds `left` elements before the
+ /// input tensor values and `right` elements after.
pub fn pad_with_zeros<D: Dim>(&self, dim: D, left: usize, right: usize) -> Result<Self> {
if left == 0 && right == 0 {
Ok(self.clone())
@@ -1884,6 +1948,7 @@ impl Tensor {
}
}
+ /// Run the `forward` method of `m` on `self`.
pub fn apply<M: crate::Module>(&self, m: &M) -> Result<Self> {
m.forward(self)
}
diff --git a/candle-datasets/Cargo.toml b/candle-datasets/Cargo.toml
index f4472a08..d69318e1 100644
--- a/candle-datasets/Cargo.toml
+++ b/candle-datasets/Cargo.toml
@@ -11,8 +11,8 @@ readme = "README.md"
[dependencies]
byteorder = { workspace = true }
-candle = { path = "../candle-core", version = "0.2.0", package = "candle-core" }
-candle-nn = { path = "../candle-nn", version = "0.2.0" }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
+candle-nn = { path = "../candle-nn", version = "0.2.1" }
hf-hub = { workspace = true}
intel-mkl-src = { workspace = true, optional = true }
memmap2 = { workspace = true }
diff --git a/candle-examples/Cargo.toml b/candle-examples/Cargo.toml
index 39d2bc72..9035eae0 100644
--- a/candle-examples/Cargo.toml
+++ b/candle-examples/Cargo.toml
@@ -11,11 +11,11 @@ readme = "README.md"
[dependencies]
accelerate-src = { workspace = true, optional = true }
-candle = { path = "../candle-core", version = "0.2.0", package = "candle-core" }
-candle-datasets = { path = "../candle-datasets", version = "0.2.0" }
-candle-nn = { path = "../candle-nn", version = "0.2.0" }
-candle-transformers = { path = "../candle-transformers", version = "0.2.0" }
-candle-flash-attn = { path = "../candle-flash-attn", version = "0.2.0", optional = true }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
+candle-datasets = { path = "../candle-datasets", version = "0.2.1" }
+candle-nn = { path = "../candle-nn", version = "0.2.1" }
+candle-transformers = { path = "../candle-transformers", version = "0.2.1" }
+candle-flash-attn = { path = "../candle-flash-attn", version = "0.2.1", optional = true }
safetensors = { workspace = true }
serde = { workspace = true }
serde_json = { workspace = true }
diff --git a/candle-examples/examples/mnist-training/main.rs b/candle-examples/examples/mnist-training/main.rs
index a90904c4..16c4bb60 100644
--- a/candle-examples/examples/mnist-training/main.rs
+++ b/candle-examples/examples/mnist-training/main.rs
@@ -242,7 +242,7 @@ struct Args {
#[arg(long)]
load: Option<String>,
- /// The file where to load the trained weights from, in safetensors format.
+ /// The directory where to load the dataset from, in ubyte format.
#[arg(long)]
local_mnist: Option<String>,
}
diff --git a/candle-flash-attn/Cargo.toml b/candle-flash-attn/Cargo.toml
index f51c277d..0d130519 100644
--- a/candle-flash-attn/Cargo.toml
+++ b/candle-flash-attn/Cargo.toml
@@ -1,6 +1,6 @@
[package]
name = "candle-flash-attn"
-version = "0.2.0"
+version = "0.2.1"
edition = "2021"
description = "Flash attention layer for the candle ML framework."
@@ -11,7 +11,7 @@ license = "MIT OR Apache-2.0"
readme = "README.md"
[dependencies]
-candle = { path = "../candle-core", features = ["cuda"], version = "0.2.0", package = "candle-core" }
+candle = { path = "../candle-core", features = ["cuda"], version = "0.2.1", package = "candle-core" }
half = { version = "2.3.1", features = ["num-traits"] }
[build-dependencies]
@@ -21,4 +21,4 @@ rayon = "1.7.0"
[dev-dependencies]
anyhow = { version = "1", features = ["backtrace"] }
-candle-nn = { path = "../candle-nn", version = "0.2.0", features = ["cuda"] }
+candle-nn = { path = "../candle-nn", version = "0.2.1", features = ["cuda"] }
diff --git a/candle-kernels/Cargo.toml b/candle-kernels/Cargo.toml
index 5f5c356e..576c52ea 100644
--- a/candle-kernels/Cargo.toml
+++ b/candle-kernels/Cargo.toml
@@ -1,6 +1,6 @@
[package]
name = "candle-kernels"
-version = "0.2.0"
+version = "0.2.1"
edition = "2021"
description = "CUDA kernels for Candle"
diff --git a/candle-nn/Cargo.toml b/candle-nn/Cargo.toml
index 7ee779f8..aa055583 100644
--- a/candle-nn/Cargo.toml
+++ b/candle-nn/Cargo.toml
@@ -11,7 +11,7 @@ readme = "README.md"
[dependencies]
accelerate-src = { workspace = true, optional = true }
-candle = { path = "../candle-core", version = "0.2.0", package = "candle-core" }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
thiserror = { workspace = true }
intel-mkl-src = { workspace = true, optional = true }
safetensors = { workspace = true }
diff --git a/candle-pyo3/Cargo.toml b/candle-pyo3/Cargo.toml
index 98c5f936..60272c9b 100644
--- a/candle-pyo3/Cargo.toml
+++ b/candle-pyo3/Cargo.toml
@@ -15,7 +15,7 @@ crate-type = ["cdylib"]
doc = false
[dependencies]
-candle = { path = "../candle-core", version = "0.2.0", package = "candle-core" }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
half = { workspace = true }
pyo3 = { version = "0.19.0", features = ["extension-module"] }
diff --git a/candle-transformers/Cargo.toml b/candle-transformers/Cargo.toml
index 7549dfa5..a05b9bb7 100644
--- a/candle-transformers/Cargo.toml
+++ b/candle-transformers/Cargo.toml
@@ -11,8 +11,8 @@ readme = "README.md"
[dependencies]
accelerate-src = { workspace = true, optional = true }
-candle = { path = "../candle-core", version = "0.2.0", package = "candle-core" }
-candle-nn = { path = "../candle-nn", version = "0.2.0" }
+candle = { path = "../candle-core", version = "0.2.1", package = "candle-core" }
+candle-nn = { path = "../candle-nn", version = "0.2.1" }
intel-mkl-src = { workspace = true, optional = true }
rand = { workspace = true }
wav = { workspace = true }
diff --git a/candle-wasm-examples/llama2-c/Cargo.toml b/candle-wasm-examples/llama2-c/Cargo.toml
index 95309e1f..d862a833 100644
--- a/candle-wasm-examples/llama2-c/Cargo.toml
+++ b/candle-wasm-examples/llama2-c/Cargo.toml
@@ -9,8 +9,8 @@ categories.workspace = true
license.workspace = true
[dependencies]
-candle = { path = "../../candle-core", version = "0.2.0", package = "candle-core" }
-candle-nn = { path = "../../candle-nn", version = "0.2.0" }
+candle = { path = "../../candle-core", version = "0.2.1", package = "candle-core" }
+candle-nn = { path = "../../candle-nn", version = "0.2.1" }
num-traits = { workspace = true }
tokenizers = { workspace = true, features = ["unstable_wasm"] }
diff --git a/candle-wasm-examples/whisper/Cargo.toml b/candle-wasm-examples/whisper/Cargo.toml
index 9578d66e..47e7e094 100644
--- a/candle-wasm-examples/whisper/Cargo.toml
+++ b/candle-wasm-examples/whisper/Cargo.toml
@@ -9,8 +9,8 @@ categories.workspace = true
license.workspace = true
[dependencies]
-candle = { path = "../../candle-core", version = "0.2.0", package = "candle-core" }
-candle-nn = { path = "../../candle-nn", version = "0.2.0" }
+candle = { path = "../../candle-core", version = "0.2.1", package = "candle-core" }
+candle-nn = { path = "../../candle-nn", version = "0.2.1" }
num-traits = { workspace = true }
tokenizers = { workspace = true, features = ["unstable_wasm"] }
diff --git a/candle-wasm-examples/yolo/Cargo.toml b/candle-wasm-examples/yolo/Cargo.toml
index cf0fbf8d..b4daf6e6 100644
--- a/candle-wasm-examples/yolo/Cargo.toml
+++ b/candle-wasm-examples/yolo/Cargo.toml
@@ -9,8 +9,8 @@ categories.workspace = true
license.workspace = true
[dependencies]
-candle = { path = "../../candle-core", version = "0.2.0", package = "candle-core" }
-candle-nn = { path = "../../candle-nn", version = "0.2.0" }
+candle = { path = "../../candle-core", version = "0.2.1", package = "candle-core" }
+candle-nn = { path = "../../candle-nn", version = "0.2.1" }
num-traits = { workspace = true }
serde = { workspace = true }
serde_json = { workspace = true }
generated by cgit v1.2.3 (git 2.39.1) at 2025-04-10 01:07:13 +0000