rel: try to test v0.2.0

.github/workflows/build-wheels.yml

@@ -4,7 +4,8 @@ on:
   push:
     branches: [main]
     tags: ["*"]
-  pull_request:
+  # Disabled for test/metatensor-v0.2.0: packaging requires released metatensor
+  # pull_request:
     paths:
       # build wheels in PR if this file changed
       - '.github/workflows/build-wheels.yml'

.github/workflows/coverage.yml

@@ -40,6 +40,18 @@ jobs:
           python -m pip install --upgrade pip
           python -m pip install tox coverage
 
+      - name: install metatensor from labels-values-array-clean branch
+        run: |
+          pip install setuptools cmake packaging wheel
+          git clone --depth 1 --branch labels-values-array-clean https://github.com/HaoZeke/metatensor.git ${{ runner.temp }}/metatensor-v020
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_core
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_operations
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_learn
+          pip install torch
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_torch
+        env:
+          PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu
+
       - name: install lcov
         run: sudo apt install -y lcov
 

.github/workflows/docs.yml

@@ -38,6 +38,18 @@ jobs:
           python -m pip install tox
           sudo apt install doxygen
 
+      - name: install metatensor from labels-values-array-clean branch
+        run: |
+          pip install setuptools cmake packaging wheel
+          git clone --depth 1 --branch labels-values-array-clean https://github.com/HaoZeke/metatensor.git ${{ runner.temp }}/metatensor-v020
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_core
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_operations
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_learn
+          pip install torch
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_torch
+        env:
+          PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu
+
       - name: build documentation
         run: tox -e docs
         env:

.github/workflows/python-tests.yml

@@ -44,6 +44,18 @@ jobs:
           python -m pip install --upgrade pip
           python -m pip install tox
 
+      - name: install metatensor from labels-values-array-clean branch
+        run: |
+          pip install setuptools cmake packaging wheel
+          git clone --depth 1 --branch labels-values-array-clean https://github.com/HaoZeke/metatensor.git ${{ runner.temp }}/metatensor-v020
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_core
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_operations
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_learn
+          pip install torch
+          METATENSOR_NO_LOCAL_DEPS=1 pip install --no-build-isolation ${{ runner.temp }}/metatensor-v020/python/metatensor_torch
+        env:
+          PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu
+
       - name: Setup sccache
         uses: mozilla-actions/sccache-action@v0.0.9
         with:
@@ -62,7 +74,6 @@ jobs:
           # Use the CPU only version of torch when building/running the code
           PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu
 
-  # second set of jobs checking that (non-test) code still compiles/run as expected
   prevent-bitrot:
     runs-on: ${{ matrix.os }}
     name: Python ${{ matrix.python-version }} / check build

featomic-torch/CMakeLists.txt

@@ -122,17 +122,17 @@ find_package(Torch 2.3 REQUIRED)
 #
 # When updating METATENSOR_TORCH_FETCH_VERSION, you will also have to update the
 # SHA256 sum of the file in `FetchContent_Declare`.
-set(METATENSOR_TORCH_FETCH_VERSION "0.8.2")
-set(REQUIRED_METATENSOR_TORCH_VERSION "0.8")
+set(METATENSOR_TORCH_FETCH_VERSION "0.9.0")
+set(REQUIRED_METATENSOR_TORCH_VERSION "0.9")
 if (FEATOMIC_FETCH_METATENSOR_TORCH)
-    message(STATUS "Fetching metatensor-torch from github")
+    message(STATUS "Fetching metatensor-torch from github (labels-values-array-clean)")
 
-    set(URL_ROOT "https://github.com/metatensor/metatensor/releases/download")
     include(FetchContent)
     FetchContent_Declare(
         metatensor_torch
-        URL      ${URL_ROOT}/metatensor-torch-v${METATENSOR_TORCH_FETCH_VERSION}/metatensor-torch-cxx-${METATENSOR_TORCH_FETCH_VERSION}.tar.gz
-        URL_HASH SHA256=0be618d0cdcfca86cd0c25f47d360b6a2410ebb09ece8d21f153e933ce64bb55
+        GIT_REPOSITORY https://github.com/HaoZeke/metatensor.git
+        GIT_TAG        labels-values-array-clean
+        SOURCE_SUBDIR  metatensor-torch
     )
 
     FetchContent_MakeAvailable(metatensor_torch)

featomic/CMakeLists.txt

@@ -246,17 +246,17 @@ endif()
 #
 # When updating METATENSOR_FETCH_VERSION, you will also have to update the
 # SHA256 sum of the file in `FetchContent_Declare`.
-set(METATENSOR_FETCH_VERSION "0.1.20")
-set(METATENSOR_REQUIRED_VERSION "0.1")
+set(METATENSOR_FETCH_VERSION "0.2.0")
+set(METATENSOR_REQUIRED_VERSION "0.2")
 if (FEATOMIC_FETCH_METATENSOR)
-    message(STATUS "Fetching metatensor-core from github")
+    message(STATUS "Fetching metatensor-core from github (labels-values-array-clean branch)")
 
     include(FetchContent)
-    set(URL_ROOT "https://github.com/metatensor/metatensor/releases/download")
     FetchContent_Declare(
         metatensor
-        URL      ${URL_ROOT}/metatensor-core-v${METATENSOR_FETCH_VERSION}/metatensor-core-cxx-${METATENSOR_FETCH_VERSION}.tar.gz
-        URL_HASH SHA256=eec78853aa8d2e91d931712242566f8ad3c03cbd291c852fb67a166bfa2e0eaa
+        GIT_REPOSITORY https://github.com/HaoZeke/metatensor.git
+        GIT_TAG        labels-values-array-clean
+        SOURCE_SUBDIR  metatensor-core
     )
 
     FetchContent_MakeAvailable(metatensor)

featomic/Cargo.toml

@@ -25,7 +25,7 @@ metatensor-static = ["metatensor/static"]
 all-features = true
 
 [dependencies]
-metatensor = {version = "0.2.2", features = ["rayon"]}
+metatensor = {git = "https://github.com/HaoZeke/metatensor.git", branch = "labels-values-array-clean", features = ["rayon"]}
 
 ndarray = {version = "0.17", features = ["rayon", "serde", "approx"]}
 num-traits = "0.2"
@@ -57,7 +57,7 @@ toml_writer = "=1.0.2"
 [build-dependencies]
 cbindgen = { version = "0.29", default-features = false }
 fs_extra = "1"
-metatensor = "0.2"
+metatensor = {git = "https://github.com/HaoZeke/metatensor.git", branch = "labels-values-array-clean"}
 
 # the last versions that supports Rust 1.74
 tempfile = "=3.24.0"

featomic/examples/compute-soap.c

@@ -1,12 +1,93 @@
 #include <assert.h>
 #include <stdbool.h>
 #include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
 
 #include <featomic.h>
 #include <metatensor.h>
 
 #include "common/systems.h"
 
+// Minimal scalar fill_value array for keys_to_samples/keys_to_properties.
+static double SCALAR_FILL_DATA = 0.0;
+static uintptr_t SCALAR_FILL_SHAPE = 1;
+
+static mts_status_t fill_shape(const void* p, const uintptr_t** shape, uintptr_t* count) {
+    (void)p; *shape = &SCALAR_FILL_SHAPE; *count = 1; return MTS_SUCCESS;
+}
+static mts_status_t fill_origin(const void* p, mts_data_origin_t* o) {
+    (void)p; mts_register_data_origin("c-scalar-fill", o); return MTS_SUCCESS;
+}
+static mts_status_t fill_device(const void* p, DLDevice* d) {
+    (void)p; d->device_type = kDLCPU; d->device_id = 0; return MTS_SUCCESS;
+}
+static mts_status_t fill_dtype(const void* p, DLDataType* dt) {
+    (void)p; dt->code = kDLFloat; dt->bits = 64; dt->lanes = 1; return MTS_SUCCESS;
+}
+
+static int64_t FILL_DL_SHAPE = 1;
+
+static mts_status_t fill_as_dlpack(void* p, DLManagedTensorVersioned** out, DLDevice dev, const int64_t* stream, DLPackVersion ver) {
+    (void)stream; (void)ver;
+    DLManagedTensorVersioned* m = (DLManagedTensorVersioned*)calloc(1, sizeof(DLManagedTensorVersioned));
+    m->version.major = DLPACK_MAJOR_VERSION;
+    m->version.minor = DLPACK_MINOR_VERSION;
+    m->dl_tensor.data = p;
+    m->dl_tensor.device.device_type = kDLCPU;
+    m->dl_tensor.device.device_id = 0;
+    m->dl_tensor.ndim = 1;
+    m->dl_tensor.shape = &FILL_DL_SHAPE;
+    m->dl_tensor.strides = NULL;
+    m->dl_tensor.byte_offset = 0;
+    m->dl_tensor.dtype.code = kDLFloat;
+    m->dl_tensor.dtype.bits = 64;
+    m->dl_tensor.dtype.lanes = 1;
+    m->deleter = (void(*)(DLManagedTensorVersioned*))free;
+    *out = m;
+    return MTS_SUCCESS;
+}
+
+static mts_array_t scalar_fill_value(void) {
+    mts_array_t array;
+    memset(&array, 0, sizeof(array));
+    array.ptr = &SCALAR_FILL_DATA;
+    array.shape = fill_shape;
+    array.origin = fill_origin;
+    array.device = fill_device;
+    array.dtype = fill_dtype;
+    array.as_dlpack = fill_as_dlpack;
+    return array;
+}
+
+// Empty i32 array with shape [0, size] for creating empty labels
+static uintptr_t EMPTY_LABELS_SHAPE[2] = {0, 0};
+
+static mts_status_t empty_labels_shape(const void* p, const uintptr_t** shape, uintptr_t* count) {
+    (void)p; *shape = EMPTY_LABELS_SHAPE; *count = 2; return MTS_SUCCESS;
+}
+static mts_status_t empty_labels_origin(const void* p, mts_data_origin_t* o) {
+    (void)p; mts_register_data_origin("c-empty-labels", o); return MTS_SUCCESS;
+}
+static mts_status_t empty_labels_device(const void* p, DLDevice* d) {
+    (void)p; d->device_type = kDLCPU; d->device_id = 0; return MTS_SUCCESS;
+}
+static mts_status_t empty_labels_dtype(const void* p, DLDataType* dt) {
+    (void)p; dt->code = kDLInt; dt->bits = 32; dt->lanes = 1; return MTS_SUCCESS;
+}
+
+static mts_array_t empty_labels_array(size_t n_dimensions) {
+    mts_array_t array;
+    memset(&array, 0, sizeof(array));
+    EMPTY_LABELS_SHAPE[0] = 0;
+    EMPTY_LABELS_SHAPE[1] = n_dimensions;
+    array.shape = empty_labels_shape;
+    array.origin = empty_labels_origin;
+    array.device = empty_labels_device;
+    array.dtype = empty_labels_dtype;
+    return array;
+}
+
 static mts_tensormap_t* move_keys_to_samples(mts_tensormap_t* descriptor, const char* keys_to_move[], size_t keys_to_move_len);
 static mts_tensormap_t* move_keys_to_properties(mts_tensormap_t* descriptor, const char* keys_to_move[], size_t keys_to_move_len);
 
@@ -111,16 +192,21 @@ int main(int argc, char* argv[]) {
         goto cleanup;
     }
 
-    status = array.data(array.ptr, &values);
-    if (status != MTS_SUCCESS) {
-        printf("Error: %s\n", mts_last_error());
-        goto cleanup;
+    {
+        DLManagedTensorVersioned* dl_managed = NULL;
+        DLDevice cpu_device = {kDLCPU, 0};
+        DLPackVersion max_ver = {DLPACK_MAJOR_VERSION, DLPACK_MINOR_VERSION};
+        status = array.as_dlpack(array.ptr, &dl_managed, cpu_device, NULL, max_ver);
+        if (status != MTS_SUCCESS) {
+            printf("Error: %s\n", mts_last_error());
+            goto cleanup;
+        }
+        values = (double*)dl_managed->dl_tensor.data;
+        if (dl_managed->deleter) {
+            dl_managed->deleter(dl_managed);
+        }
     }
 
-    if (status != MTS_SUCCESS) {
-        printf("Error: %s\n", mts_last_error());
-        goto cleanup;
-    }
     assert(shape_count == 2);
 
     // you can now use `values` as the input of a machine learning algorithm
@@ -142,31 +228,43 @@ int main(int argc, char* argv[]) {
 
 
 mts_tensormap_t* move_keys_to_samples(mts_tensormap_t* descriptor, const char* keys_to_move[], size_t keys_to_move_len) {
-    mts_labels_t keys = {0};
     mts_tensormap_t* moved_descriptor = NULL;
 
-    keys.names = keys_to_move;
-    keys.size = keys_to_move_len;
-    keys.values = NULL;
-    keys.count = 0;
+    // Create empty labels with the given dimension names and an empty array
+    mts_array_t empty_values = empty_labels_array(keys_to_move_len);
+    mts_labels_t* keys = mts_labels_create(keys_to_move, keys_to_move_len, empty_values);
+    if (keys == NULL) {
+        printf("Error creating labels: %s\n", mts_last_error());
+        mts_tensormap_free(descriptor);
+        return NULL;
+    }
 
-    moved_descriptor = mts_tensormap_keys_to_samples(descriptor, keys, true);
+    // Create an empty fill_value array (not used when all blocks have same properties)
+    mts_array_t fill_value = scalar_fill_value();
+    moved_descriptor = mts_tensormap_keys_to_samples(descriptor, keys, fill_value, true);
+    mts_labels_free(keys);
     mts_tensormap_free(descriptor);
 
     return moved_descriptor;
 }
 
 
 mts_tensormap_t* move_keys_to_properties(mts_tensormap_t* descriptor, const char* keys_to_move[], size_t keys_to_move_len) {
-    mts_labels_t keys = {0};
     mts_tensormap_t* moved_descriptor = NULL;
 
-    keys.names = keys_to_move;
-    keys.size = keys_to_move_len;
-    keys.values = NULL;
-    keys.count = 0;
+    // Create empty labels with the given dimension names and an empty array
+    mts_array_t empty_values = empty_labels_array(keys_to_move_len);
+    mts_labels_t* keys = mts_labels_create(keys_to_move, keys_to_move_len, empty_values);
+    if (keys == NULL) {
+        printf("Error creating labels: %s\n", mts_last_error());
+        mts_tensormap_free(descriptor);
+        return NULL;
+    }
 
-    moved_descriptor = mts_tensormap_keys_to_properties(descriptor, keys, true);
+    // Create an empty fill_value array (not used when all blocks have same properties)
+    mts_array_t fill_value = scalar_fill_value();
+    moved_descriptor = mts_tensormap_keys_to_properties(descriptor, keys, fill_value, true);
+    mts_labels_free(keys);
     mts_tensormap_free(descriptor);
 
     return moved_descriptor;

featomic/examples/compute-soap.rs

@@ -62,7 +62,7 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
 
     // descriptor now contains a single block, which can be used as the input
     // to standard ML algorithms
-    let values = descriptor.block_by_id(0).values().to_array();
+    let values = descriptor.block_by_id(0).values().to_ndarray();
     println!("SOAP representation shape: {:?}", values.shape());
 
     Ok(())