ok i think the openmp one works now

.devcontainer/devcontainer.json

@@ -1,26 +1,42 @@
 // For format details, see https://aka.ms/devcontainer.json. For config options, see the
 // README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-dockerfile
 {
-	"name": "Existing Dockerfile",
+  "name": "Existing Dockerfile",
-	"build": {
+  "build": {
-		// Sets the run context to one level up instead of the .devcontainer folder.
+    // Sets the run context to one level up instead of the .devcontainer folder.
-		"context": "..",
+    "context": "..",
-		// Update the 'dockerFile' property if you aren't using the standard 'Dockerfile' filename.
+    // Update the 'dockerFile' property if you aren't using the standard 'Dockerfile' filename.
-		"dockerfile": "../Dockerfile"
+    "dockerfile": "../Dockerfile"
-	}
+  },
 
-	// Features to add to the dev container. More info: https://containers.dev/features.
+  // Features to add to the dev container. More info: https://containers.dev/features.
-	// "features": {},
+  "features": {},
+  "customizations": {
+    "vscode": {
+      "extensions": [
+		"eamodio.gitlens",
+		"esbenp.prettier-vscode",
+		"llvm-vs-code-extensions.vscode-clangd",
+		"ms-azuretools.vscode-docker",
+		"ms-python.python",
+		"ms-python.vscode-pylance",
+		"ms-vscode.cpptools",
+		"ms-vscode.makefile-tools",
+		"rust-lang.rust-analyzer",
+		"tomoki1207.pdf"
+	]
+    }
+  }
 
-	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+  // Use 'forwardPorts' to make a list of ports inside the container available locally.
-	// "forwardPorts": [],
+  // "forwardPorts": [],
 
-	// Uncomment the next line to run commands after the container is created.
+  // Uncomment the next line to run commands after the container is created.
-	// "postCreateCommand": "cat /etc/os-release",
+  // "postCreateCommand": "cat /etc/os-release",
 
-	// Configure tool-specific properties.
+  // Configure tool-specific properties.
-	// "customizations": {},
+  // "customizations": {},
 
-	// Uncomment to connect as an existing user other than the container default. More info: https://aka.ms/dev-containers-non-root.
+  // Uncomment to connect as an existing user other than the container default. More info: https://aka.ms/dev-containers-non-root.
-	// "remoteUser": "devcontainer"
+  // "remoteUser": "devcontainer"
 }

.vscode/settings.json

@@ -1,5 +1,9 @@
 {
   "files.associations": {
     "common.h": "c"
-  }
+  },
+  "[python]": {
+    "editor.defaultFormatter": "ms-python.black-formatter"
+  },
+  "python.formatting.provider": "none"
 }

Dockerfile

@@ -1,4 +1,19 @@
 FROM ubuntu:22.04
+ENV PATH="/root/.cargo/bin:${PATH}"
 
 RUN apt update -y && apt install -y --no-install-recommends \
-    git make gcc valgrind
+    build-essential \
+    ca-certificates \
+    clangd \
+    curl \
+    direnv \
+    git \
+    libomp-dev \
+    python3 \
+    python3-pip \
+    valgrind \
+    ;
+RUN pip install poetry
+
+RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
+RUN echo 'eval "$(direnv hook bash)"' >> /root/.bashrc

assignments/01/.clangd

@@ -1,2 +1,2 @@
 CompileFlags:
-    Add: -I/opt/homebrew/opt/libomp/include
+    Add: -I/opt/homebrew/opt/libomp/include -I/usr/lib/gcc/aarch64-linux-gnu/11/include

assignments/01/.envrc

@@ -1,2 +1,2 @@
 export BASE_PATH=$PWD
-export CC=clang-17
+# export CC=clang-17

assignments/01/Makefile

@@ -1,13 +1,20 @@
 .PHONY: all watch-openmp clean
 
-CFLAGS := -std=c11 -fopenmp -I/opt/homebrew/opt/libomp/include -g
+CFLAGS := -std=c11 -fopenmp \
-LDFLAGS :=  -std=c11 -fopenmp -L/opt/homebrew/opt/libomp/lib -g
+	-I/opt/homebrew/opt/libomp/include \
+	-I/usr/lib/gcc/aarch64-linux-gnu/11/include \
+	-O3
+LDFLAGS :=  -std=c11 -fopenmp -L/opt/homebrew/opt/libomp/lib -O3
 RUST_SOURCES := $(shell find . -name "*.rs")
 
 all: lc_openmp lc_pthreads
 
 clean:
-	rm -rf lc_openmp lc_pthreads zhan4854 zhan4854.tar.gz *.o
+	rm -rf \
+		lc_openmp lc_pthreads \
+		zhan4854 zhan4854.tar.gz \
+		dataset/small \
+		*.o
 
 zhan4854.tar.gz: common.c common.h lc_openmp.c lc_pthreads.c Makefile
 	mkdir -p zhan4854
@@ -15,9 +22,6 @@ zhan4854.tar.gz: common.c common.h lc_openmp.c lc_pthreads.c Makefile
 	tar -czvf $@ zhan4854
 	rm -r zhan4854
 
-watch-openmp:
-	watchexec -c clear -e Makefile,c,h 'make lc_openmp && ./lc_openmp ./dataset/small_data.csv ./dataset/small_label.csv 10 2'
-
 lc_openmp: lc_openmp.o common.o
 	$(CC) $(CFLAGS) $(LDFLAGS) -o $@ $^
 
@@ -27,5 +31,22 @@ lc_pthreads: lc_pthreads.o common.o
 %.o: %.c
 	$(CC) $(CFLAGS) -o $@ -c $<
 
+## Dumb debug stuff, please ignore:
+
+dataset/small/%.txt: generate_test_data.py
+	python generate_test_data.py dataset/small_data.csv dataset/small_label.csv dataset/small
+
+dataset/mnist/%.txt: generate_test_data.py
+	python generate_test_data.py dataset/MNIST_data.csv dataset/MNIST_label.csv dataset/mnist
+
+watch-openmp:
+	watchexec -c clear -e Makefile,c,h 'make lc_openmp && ./lc_openmp ./dataset/small_data.csv ./dataset/small_label.csv 10 2'
+
+run-openmp-small: lc_openmp dataset/small/train_data.txt
+	./lc_openmp dataset/small/train_data.txt dataset/small/train_label.txt 10 2 dataset/small/test_data.txt dataset/small/test_label.txt
+
+run-openmp-mnist: lc_openmp dataset/mnist/train_data.txt
+	./lc_openmp dataset/mnist/train_data.txt dataset/mnist/train_label.txt 10 2 dataset/mnist/test_data.txt dataset/mnist/test_label.txt
+
 rust: $(RUST_SOURCES)
 	cargo run -- ${BASE_PATH}/dataset/{small_data.csv,small_label.csv} 10 2

assignments/01/generate_test_data.py

@@ -1,20 +1,68 @@
+import numpy as np
 import random
 import click
+import pathlib
 
 def evaluate(w, p):
     result = sum(map(lambda s: s[0] * s[1], zip(w, p)))
     return result
 
 @click.command()
-@click.option('--dimensions', default=2, help='Number of dimensions')
+@click.argument('data_path')
-@click.option('--count', default=2000, help='How many points to generate')
+@click.argument('label_path')
-def generate_test_data(dimensions: int, count: int):
+@click.argument('out_path')
-    actual_w = [random.uniform(0.0, 1.0) for _ in range(dimensions)]
+def generate_test_data(data_path: str, label_path: str, out_path: str):
-    
+    with open(data_path, "r") as f:
-    for _ in range(count):
+        desc = f.readline().strip()
-        point = [random.uniform(0.0, 1.0) for _ in range(dimensions)]
+        rows, dimensions = map(int, desc.split())
-        y = evaluate(actual_w, point)
+        data = np.loadtxt(f)
-        print(point, y)
+    print("loaded data")
+
+    with open(label_path, "r") as f:
+        desc = f.readline().strip()
+        rows = int(desc)
+        labels = np.loadtxt(f)
+    print("loaded labels")
+
+    indices = list(range(rows))
+    random.shuffle(indices)
+    split_at = int(0.7 * rows)
+    train_indices = indices[:split_at]
+    test_indices = indices[split_at:]
+    # print("WTF?", train_indices, test_indices)
+
+    train_data = data[train_indices,:]
+    train_label = labels[train_indices]
+
+    test_data = data[test_indices,:]
+    test_label = labels[test_indices]
+
+    out_path2 = pathlib.Path(out_path)
+    out_path2.mkdir(exist_ok=True, parents=True)
+
+    with open(out_path2 / "train_data.txt", "w") as f:
+        f.write(f"{len(train_data)} {dimensions}\n")
+        for row in train_data:
+            for i, cell in enumerate(row):
+                if i > 0: f.write(" ")
+                f.write(str(cell))
+            f.write("\n")
+    with open(out_path2 / "test_data.txt", "w") as f:
+        f.write(f"{len(test_data)} {dimensions}\n")
+        for row in test_data:
+            for i, cell in enumerate(row):
+                if i > 0: f.write(" ")
+                f.write(str(cell))
+            f.write("\n")
+
+    with open(out_path2 / "train_label.txt", "w") as f:
+        f.write(f"{len(train_label)}\n")
+        for cell in train_label:
+            f.write(f"{cell}\n")
+    with open(out_path2 / "test_label.txt", "w") as f:
+        f.write(f"{len(test_label)}\n")
+        for cell in test_label:
+            f.write(f"{cell}\n")
 
 if __name__ == '__main__':
     generate_test_data()

assignments/01/lc_openmp.c

@@ -7,6 +7,13 @@
 #include "common.h"
 
 int main(int argc, char **argv) {
+  if (argc < 5) {
+    fprintf(stderr,
+            "USAGE: %s data_file label_file outer_iterations thread_count",
+            argv[0]);
+    exit(1);
+  }
+
   char *data_file_name = argv[1], *label_file_name = argv[2];
   int outer_iterations = atoi(argv[3]);
   int thread_count = atoi(argv[4]);
@@ -15,6 +22,13 @@ int main(int argc, char **argv) {
 
   struct data *data = read_data(data_file_name);
   struct labels *label = read_labels(label_file_name);
+
+  // NAN CHECK
+  for (int i = 0; i < data->dimensions * data->rows; i++) {
+    if (isnan(data->buf[i]))
+      printf("failed at index %d\n", i);
+  }
+
   printf("Running %d iteration(s) with %d thread(s).\n", outer_iterations,
          thread_count);
 
@@ -28,11 +42,11 @@ int main(int argc, char **argv) {
 #pragma omp parallel for default(shared)
     for (int i = 0; i < data->dimensions; i++) {
 
-#pragma omp parallel for default(shared)
+      // #pragma omp parallel for default(shared)
       for (int j = 0; j < data->rows; j++) {
         FLOAT x_ni_w_ni = 0;
 
-#pragma omp parallel for default(shared) reduction(+ : x_ni_w_ni)
+        // #pragma omp parallel for default(shared) reduction(+ : x_ni_w_ni)
         for (int i2 = 0; i2 < data->dimensions; i2++) {
           if (i2 == i)
             continue;
@@ -40,40 +54,72 @@ int main(int argc, char **argv) {
           x_ni_w_ni = data->buf[data->rows * i2 + j] * w[i2];
         }
 
-        ouais[data->dimensions * i + j] = label->buf[j] - x_ni_w_ni;
+        ouais[data->rows * i + j] = label->buf[j] - x_ni_w_ni;
       }
 
       FLOAT numer = 0, denom = 0;
 
-#pragma omp parallel for default(shared) reduction(+ : numer, denom)
+      // #pragma omp parallel for default(shared) reduction(+ : numer, denom)
       for (int j = 0; j < data->rows; j++) {
-        FLOAT xij = data->buf[data->dimensions * i + j];
+        FLOAT xij = data->buf[data->rows * i + j];
-        numer = xij * ouais[data->dimensions * i + j];
+        numer += xij * ouais[data->rows * i + j];
-        denom = xij * xij;
+        denom += xij * xij;
       }
 
-      new_w[i] = numer / denom;
+      if (denom == 0) {
+        new_w[i] = 0;
+        // printf("wtf? %f\n", numer);
+      } else
+        new_w[i] = numer / denom;
     }
 
-    printf("Done.\n");
-    for (int idx = 0; idx < data->dimensions; idx++) {
-      printf("%.3f ", new_w[idx]);
-    }
-    printf("\n");
-
-    memcpy(w, new_w, sizeof(w));
-
     double end_time = monotonic_seconds();
     print_time(end_time - start_time);
+
+    printf("Done.\nw = [");
+    for (int idx = 0; idx < data->dimensions; idx++) {
+      w[idx] = new_w[idx];
+      printf("%.3f ", w[idx]);
+    }
+    printf("]\n");
+
+    // memcpy(w, new_w, data->dimensions * sizeof(FLOAT));
   }
 
   free(ouais);
-  free(w);
   free(new_w);
   free(data->buf);
   free(label->buf);
   free(data);
   free(label);
 
+  // NOTE: NOT PART OF THE ASSIGNMENT
+  // Perform testing to ensure that the training actually works
+
+  if (argc >= 7) {
+    struct data *test_data = read_data(argv[5]);
+    struct labels *test_label = read_labels(argv[6]);
+
+    int num_correct = 0;
+    for (int j = 0; j < test_data->rows; j++) {
+      FLOAT output = 0;
+      for (int i = 0; i < test_data->dimensions; i++) {
+        output += test_data->buf[test_data->rows * i + j] * w[i];
+      }
+
+      // printf("expected: %f, actual: %f\n", test_label->buf[j], output);
+      FLOAT correct_answer = test_label->buf[j];
+      FLOAT incorrect_answer = -correct_answer;
+
+      if (fabs(output - correct_answer) < fabs(output - incorrect_answer))
+        num_correct += 1;
+    }
+
+    printf("num correct: %d, out of %d (%.2f%%)\n", num_correct,
+           test_data->rows, (100.0 * num_correct) / test_data->rows);
+  }
+
+  free(w);
+
   return 0;
 }

assignments/01/lc_pthreads.c

@@ -1,3 +1,18 @@
+#include <stdio.h>
+
 #include "common.h"
 
-int main() { return 0; }
+int main(int argc, char **argv) {
+  if (argc < 5) {
+    fprintf(stderr,
+            "USAGE: %s data_file label_file outer_iterations thread_count",
+            argv[0]);
+    exit(1);
+  }
+
+  char *data_file_name = argv[1], *label_file_name = argv[2];
+  int outer_iterations = atoi(argv[3]);
+  int thread_count = atoi(argv[4]);
+
+  return 0;
+}

assignments/01/main.py

@@ -16,9 +16,12 @@ print("loaded labels")
 print(data.shape)
 print(labels.shape)
 
-w = np.empty((dimensions, 1))
+w = np.zeros(dimensions)
-new_w = np.empty(w.shape)
+print(w)
+
+np.set_printoptions(precision=3)
 for _ in range(10):
+    new_w = np.empty(w.shape)
     for i in range(dimensions):
         data_ni = np.delete(data, i, axis=1)
         w_ni = np.delete(w, i)
@@ -26,9 +29,10 @@ for _ in range(10):
         res = data_ni @ w_ni
 
         x_i = data[:,i]
-        numer = x_i.transpose() @ (labels - np.matmul(data_ni, w_ni))
+        numer = x_i.transpose() @ (labels - res)
         denom = x_i.transpose() @ x_i
 
         new_w[i] = numer / denom
-    w = new_w
+
-    print("w", new_w)
+    print("new_w", np.round(new_w, 3))
+    w = new_w

assignments/01/poetry.lock

@@ -25,7 +25,48 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "numpy"
+version = "1.26.0"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = "<3.13,>=3.9"
+files = [
+    {file = "numpy-1.26.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f8db2f125746e44dce707dd44d4f4efeea8d7e2b43aace3f8d1f235cfa2733dd"},
+    {file = "numpy-1.26.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0621f7daf973d34d18b4e4bafb210bbaf1ef5e0100b5fa750bd9cde84c7ac292"},
+    {file = "numpy-1.26.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:51be5f8c349fdd1a5568e72713a21f518e7d6707bcf8503b528b88d33b57dc68"},
+    {file = "numpy-1.26.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:767254ad364991ccfc4d81b8152912e53e103ec192d1bb4ea6b1f5a7117040be"},
+    {file = "numpy-1.26.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:436c8e9a4bdeeee84e3e59614d38c3dbd3235838a877af8c211cfcac8a80b8d3"},
+    {file = "numpy-1.26.0-cp310-cp310-win32.whl", hash = "sha256:c2e698cb0c6dda9372ea98a0344245ee65bdc1c9dd939cceed6bb91256837896"},
+    {file = "numpy-1.26.0-cp310-cp310-win_amd64.whl", hash = "sha256:09aaee96c2cbdea95de76ecb8a586cb687d281c881f5f17bfc0fb7f5890f6b91"},
+    {file = "numpy-1.26.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:637c58b468a69869258b8ae26f4a4c6ff8abffd4a8334c830ffb63e0feefe99a"},
+    {file = "numpy-1.26.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:306545e234503a24fe9ae95ebf84d25cba1fdc27db971aa2d9f1ab6bba19a9dd"},
+    {file = "numpy-1.26.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c6adc33561bd1d46f81131d5352348350fc23df4d742bb246cdfca606ea1208"},
+    {file = "numpy-1.26.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e062aa24638bb5018b7841977c360d2f5917268d125c833a686b7cbabbec496c"},
+    {file = "numpy-1.26.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:546b7dd7e22f3c6861463bebb000646fa730e55df5ee4a0224408b5694cc6148"},
+    {file = "numpy-1.26.0-cp311-cp311-win32.whl", hash = "sha256:c0b45c8b65b79337dee5134d038346d30e109e9e2e9d43464a2970e5c0e93229"},
+    {file = "numpy-1.26.0-cp311-cp311-win_amd64.whl", hash = "sha256:eae430ecf5794cb7ae7fa3808740b015aa80747e5266153128ef055975a72b99"},
+    {file = "numpy-1.26.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:166b36197e9debc4e384e9c652ba60c0bacc216d0fc89e78f973a9760b503388"},
+    {file = "numpy-1.26.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f042f66d0b4ae6d48e70e28d487376204d3cbf43b84c03bac57e28dac6151581"},
+    {file = "numpy-1.26.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e5e18e5b14a7560d8acf1c596688f4dfd19b4f2945b245a71e5af4ddb7422feb"},
+    {file = "numpy-1.26.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f6bad22a791226d0a5c7c27a80a20e11cfe09ad5ef9084d4d3fc4a299cca505"},
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+    {file = "numpy-1.26.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4a873a8180479bc829313e8d9798d5234dfacfc2e8a7ac188418189bb8eafbd2"},
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+    {file = "numpy-1.26.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c78a22e95182fb2e7874712433eaa610478a3caf86f28c621708d35fa4fd6e7f"},
+    {file = "numpy-1.26.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86f737708b366c36b76e953c46ba5827d8c27b7a8c9d0f471810728e5a2fe57c"},
+    {file = "numpy-1.26.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b44e6a09afc12952a7d2a58ca0a2429ee0d49a4f89d83a0a11052da696440e49"},
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+    {file = "numpy-1.26.0-cp39-cp39-win_amd64.whl", hash = "sha256:020cdbee66ed46b671429c7265cf00d8ac91c046901c55684954c3958525dab2"},
+    {file = "numpy-1.26.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:0792824ce2f7ea0c82ed2e4fecc29bb86bee0567a080dacaf2e0a01fe7654369"},
+    {file = "numpy-1.26.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7d484292eaeb3e84a51432a94f53578689ffdea3f90e10c8b203a99be5af57d8"},
+    {file = "numpy-1.26.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:186ba67fad3c60dbe8a3abff3b67a91351100f2661c8e2a80364ae6279720299"},
+    {file = "numpy-1.26.0.tar.gz", hash = "sha256:f93fc78fe8bf15afe2b8d6b6499f1c73953169fad1e9a8dd086cdff3190e7fdf"},
+]
+
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.11"
+python-versions = ">=3.10,<3.13"
-content-hash = "628b2f91879695db7c6062f64a17355697ff1237691b4f4f3105875e3b3eb929"
+content-hash = "bddb5c36e945042dc9b3146b4a98b8bc383ce35a00ae8ca34fa85d5641790862"

assignments/01/pyproject.toml

@@ -6,8 +6,9 @@ authors = ["Michael Zhang <mail@mzhang.io>"]
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.11"
+python = ">=3.10,<3.13"
 click = "^8.1.7"
+numpy = "^1.26.0"
 
 
 [build-system]

assignments/01/run_mnist_dataset.sh

@@ -0,0 +1,5 @@
+#!/usr/bin/env bash
+exec "$1" \
+    $BASE_PATH/dataset/MNIST_data.csv \
+    $BASE_PATH/dataset/MNIST_label.csv \
+    10 2

assignments/01/run_small_dataset.sh

@@ -0,0 +1,5 @@
+#!/usr/bin/env bash
+exec "$1" \
+    $BASE_PATH/dataset/small_data.csv \
+    $BASE_PATH/dataset/small_label.csv \
+    10 2

assignments/01/rust/src/lolspan.rs

@@ -1,8 +1,9 @@
+use std::fmt::Debug;
 use std::{marker::PhantomData, ops::Index};
 pub struct Span<'a, T, F, U = usize>(&'a [T], F, PhantomData<U>);
 
 impl<'a, T, F, U> Span<'a, T, F, U> {
-  pub fn new(slice: &[T], func: F) -> Self {
+  pub fn new(slice: &'a [T], func: F) -> Self {
     Span(slice, func, PhantomData::default())
   }
 }
@@ -10,12 +11,16 @@ impl<'a, T, F, U> Span<'a, T, F, U> {
 impl<'a, T, F, U> Index<U> for Span<'a, T, F, U>
 where
   F: Fn(U) -> usize,
+  U: Debug,
 {
   type Output = T;
 
+  #[inline]
   fn index(&self, index: U) -> &Self::Output {
-    let index = (self.1)(index);
+    // print!("transformed {index:?}");
-    &self.0[index]
+    let transformed_index = (self.1)(index);
+    // println!(" into {transformed_index:?}");
+    &self.0[transformed_index]
   }
 }
 
@@ -24,7 +29,7 @@ fn test() {
   let w = (0..100).collect::<Vec<_>>();
 
   // Exclude #4
-  let w_i_inv: Span<_, _, usize> = Span(w, fuck::<4>, PhantomData::default());
+  let w_i_inv: Span<_, _, usize> = Span(&w, fuck::<4>, PhantomData::default());
 
   for i in 0..99 {
     let n = w_i_inv[i];

assignments/01/rust/src/main.rs

@@ -29,6 +29,14 @@ struct Data {
   dimensions: usize,
   buf: Vec<f64>,
 }
+
+impl Data {
+  #[inline]
+  fn get(&self, i: usize, j: usize) -> f64 {
+    self.buf[self.rows * i + j]
+  }
+}
+
 struct Label {
   num_points: usize,
   buf: Vec<f64>,
@@ -44,21 +52,11 @@ fn main() -> Result<()> {
 
   for _ in 0..opt.outer_iterations {
     let new_w = (0..data.dimensions)
-      .par_bridge()
+      // .par_bridge()
       .map(|i| {
-        let x_i_start = data.rows * i;
+        // let x_i_start = data.rows * i;
-        let x_i_end = data.rows * (i + 1);
+        // let x_i_end = data.rows * (i + 1);
-        let x_i = &data.buf[x_i_start..x_i_end];
+        // let x_i = &data.buf[x_i_start..x_i_end];
-
-        let missing_i = i;
-        let data_ni: Span<f64, _, (usize, usize)> =
-          Span::new(&data.buf, |(j2, i2): (usize, usize)| {
-            data.buf
-              [data.rows * (if i2 >= missing_i { i2 + 1 } else { i2 }) + j2]
-          });
-        let w_ni: Span<f64, _, usize> = Span::new(&w, |i2: usize| {
-          w[if i2 >= missing_i { i2 + 1 } else { i2 }]
-        });
 
         // X = n x m
         // y = n x 1
@@ -69,13 +67,15 @@ fn main() -> Result<()> {
         // X_ni_w_ni = n x 1
 
         let x_ni_w_ni = (0..data.rows)
-          .par_bridge()
+          // .par_bridge()
           .map(|j| {
             (0..data.dimensions)
-              .filter(|i| *i != missing_i)
+              .filter(|i2| *i2 != i)
               .par_bridge()
-              .map(|i| data_ni[(j, i)] * w_ni[i])
+              .map(|i| data.get(i, j) * w[i])
-              .reduce(|| 0.0, |a, b| a + b)
+              .sum::<f64>()
+
+            // label.buf[j] - result
           })
           .collect::<Vec<_>>();
 
@@ -86,18 +86,29 @@ fn main() -> Result<()> {
           .map(|(y, x)| y - x)
           .collect::<Vec<_>>();
 
-        // combine
+        let (numer, denom) = (0..data.rows)
-        let numer = x_i
+          .par_bridge()
-          .par_iter()
+          .map(|j| {
-          .zip(sub.par_iter())
+            let xij = data.get(i, j);
-          .map(|(x, y)| x * y)
+            let num = xij * sub[j];
-          .reduce(|| 0.0, |x, y| x + y);
+            let den = xij * xij;
+            (num, den)
+          })
+          .reduce(|| (0.0, 0.0), |(n1, d1), (n2, d2)| (n1 + d1, n2 + d2));
+        // .unwrap();
 
-        let denom = x_i
+        // combine
-          .par_iter()
+        // let numer = x_i
-          .zip(x_i.par_iter())
+        //   .par_iter()
-          .map(|(a, b)| a * b)
+        //   .zip(sub.par_iter())
-          .reduce(|| 0.0, |x, y| x + y);
+        //   .map(|(x, y)| x * y)
+        //   .reduce(|| 0.0, |x, y| x + y);
+
+        // let denom = x_i
+        //   .par_iter()
+        //   .zip(x_i.par_iter())
+        //   .map(|(a, b)| a * b)
+        //   .reduce(|| 0.0, |x, y| x + y);
 
         return numer / denom;
       })
@@ -107,7 +118,6 @@ fn main() -> Result<()> {
     println!("w is {w:?}");
   }
 
-  println!("Hello, world!");
   Ok(())
 }