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ggml : unit test for quantization functions (#953)
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* Unit test for quantization functions

Use the ggml_internal_get_quantize_fn function to loop through all
quantization formats and run a sanity check on the result.

Also add a microbenchmark that times these functions directly without
running the rest of the GGML graph.

* test-quantize-fns: CI fixes

Fix issues uncovered in CI
 - need to use sizes divisible by 32*8 for loop unrolling
 - use intrinsic header that should work on Mac

* test-quantize: remove

Per PR comment, subsumed by test-quantize-fns

* test-quantize: fix for q8_0 intermediates
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unbounded authored Apr 22, 2023
1 parent 36b4f7e commit 5f93949
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3 changes: 2 additions & 1 deletion tests/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -6,5 +6,6 @@ function(llama_add_test source)
endfunction()

# llama_add_test(test-double-float.c) # SLOW
llama_add_test(test-quantize.c)
llama_add_test(test-quantize-fns.cpp)
llama_add_test(test-quantize-perf.cpp)
llama_add_test(test-tokenizer-0.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab.bin)
154 changes: 154 additions & 0 deletions tests/test-quantize-fns.cpp
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// Unit tests for quantization specific functions - quantize, dequantize and dot product

#include "ggml.h"

#undef NDEBUG
#include <assert.h>
#include <math.h>
#include <stdio.h>
#include <string>
#include <vector>


const float MAX_QUANTIZATION_REFERENCE_ERROR = 0.0001;
const float MAX_QUANTIZATION_TOTAL_ERROR = 0.002;
const float MAX_DOT_PRODUCT_ERROR = 0.02;

const char* RESULT_STR[] = {"ok", "FAILED"};


// Generate synthetic data
void generate_data(float offset, size_t n, float * dst) {
for (size_t i = 0; i < n; i++) {
dst[i] = 0.1 + 2*cosf(i + offset);
}
}

// Calculate RMSE between two float arrays
float array_rmse(const float * a1, const float * a2, size_t n) {
double sum = 0;
for (size_t i = 0; i < n; i++) {
double diff = a1[i] - a2[i];
sum += diff * diff;
}
return sqrtf(sum) / n;
}

// Total quantization error on test data
float total_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
std::vector<uint8_t> tmp_q(test_size);
std::vector<float> tmp_out(test_size);

qfns.quantize_row_q(test_data, tmp_q.data(), test_size);
qfns.dequantize_row_q(tmp_q.data(), tmp_out.data(), test_size);
return array_rmse(test_data, tmp_out.data(), test_size);
}

// Total quantization error on test data
float reference_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
std::vector<uint8_t> tmp_q(test_size);
std::vector<float> tmp_out(test_size);
std::vector<float> tmp_out_ref(test_size);

qfns.quantize_row_q(test_data, tmp_q.data(), test_size);
qfns.dequantize_row_q(tmp_q.data(), tmp_out.data(), test_size);

qfns.quantize_row_q_reference(test_data, tmp_q.data(), test_size);
qfns.dequantize_row_q(tmp_q.data(), tmp_out_ref.data(), test_size);

return array_rmse(tmp_out.data(), tmp_out_ref.data(), test_size);
}

float dot_product(const float * a1, const float * a2, size_t test_size) {
double sum = 0;
for (size_t i = 0; i < test_size; i++) {
sum += a1[i] * a2[i];
}
return sum;
}

// Total dot product error
float dot_product_error(quantize_fns_t & qfns, size_t test_size, const float * test_data1, const float *test_data2) {
std::vector<uint8_t> tmp_q1(test_size);
std::vector<uint8_t> tmp_q2(test_size*2);

qfns.quantize_row_q(test_data1, tmp_q1.data(), test_size);
qfns.quantize_row_q_dot(test_data2, tmp_q2.data(), test_size);

float result = INFINITY;
qfns.vec_dot_q(test_size, &result, tmp_q1.data(), tmp_q2.data());

const float dot_ref = dot_product(test_data1, test_data2, test_size);

return fabsf(result - dot_ref) / test_size;
}

int main(int argc, char * argv[]) {
bool verbose = false;
const size_t test_size = 32 * 128;

std::string arg;
for (int i = 1; i < argc; i++) {
arg = argv[i];

if (arg == "-v") {
verbose = true;
} else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
return 1;
}
}

std::vector<float> test_data(test_size);
std::vector<float> test_data2(test_size);

generate_data(0.0, test_data.size(), test_data.data());
generate_data(1.0, test_data2.size(), test_data2.data());

// Initialize GGML, ensures float conversion tables are initialized
struct ggml_init_params ggml_params = {
/* .mem_size = */ 1*1024,
/* .mem_buffer = */ NULL,
/* .no_alloc = */ true,
};
struct ggml_context * ctx = ggml_init(ggml_params);

int num_failed = 0;
bool failed = false;

for (int i = 0; i < GGML_TYPE_COUNT; i++) {
ggml_type type = (ggml_type) i;
quantize_fns_t qfns = ggml_internal_get_quantize_fn(i);

if (qfns.quantize_row_q) {
const float total_error = total_quantization_error(qfns, test_size, test_data.data());
failed = !(total_error < MAX_QUANTIZATION_TOTAL_ERROR);
num_failed += failed;
if (failed || verbose) {
printf("%5s absolute quantization error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], total_error);
}

const float reference_error = reference_quantization_error(qfns, test_size, test_data.data());
failed = !(reference_error < MAX_QUANTIZATION_REFERENCE_ERROR);
num_failed += failed;
if (failed || verbose) {
printf("%5s reference implementation error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], reference_error);
}

const float vec_dot_error = dot_product_error(qfns, test_size, test_data.data(), test_data2.data());
failed = !(vec_dot_error < MAX_DOT_PRODUCT_ERROR);
num_failed += failed;
if (failed || verbose) {
printf("%5s dot product error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], vec_dot_error);
}
}
}

if (num_failed || verbose) {
printf("%d tests failed\n", num_failed);
}

ggml_free(ctx);

return num_failed > 0;
}
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