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TheTomTheTom
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Merge: ci: fix turbo build + test failures (#66)
ci: fix turbo build + test failures on feature/turboquant-kv-cache
2 parents 840f3d9 + 7bf419e commit 45f8a06

3 files changed

Lines changed: 40 additions & 20 deletions

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‎ggml/src/ggml-cpu/ops.cpp‎

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -5594,6 +5594,9 @@ void ggml_compute_forward_clamp(
55945594
case GGML_TYPE_TQ2_0:
55955595
case GGML_TYPE_TQ3_1S:
55965596
case GGML_TYPE_TQ4_1S:
5597+
case GGML_TYPE_TURBO2_0:
5598+
case GGML_TYPE_TURBO3_0:
5599+
case GGML_TYPE_TURBO4_0:
55975600
case GGML_TYPE_IQ2_XXS:
55985601
case GGML_TYPE_IQ2_XS:
55995602
case GGML_TYPE_IQ3_XXS:

‎ggml/src/ggml-cuda/turbo-quant.cuh‎

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -176,10 +176,10 @@ static void turbo_innerq_init(void) {
176176
// Zero accumulators and set calibrating flag on device
177177
float zeros[INNERQ_MAX_CHANNELS] = {0};
178178
int zero = 0, one = 1;
179-
cudaMemcpyToSymbol(d_innerq_sq_accum, zeros, sizeof(zeros));
180-
cudaMemcpyToSymbol(d_innerq_count, &zero, sizeof(int));
181-
cudaMemcpyToSymbol(d_innerq_active, &zero, sizeof(int));
182-
cudaMemcpyToSymbol(d_innerq_calibrating, &one, sizeof(int));
179+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_sq_accum, zeros, sizeof(zeros)));
180+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_count, &zero, sizeof(int)));
181+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_active, &zero, sizeof(int)));
182+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_calibrating, &one, sizeof(int)));
183183

184184
GGML_LOG_INFO("%s: InnerQ calibration started (target=%d tokens, strength=%.2f)\n",
185185
__func__, innerq_target_tokens, innerq_strength);
@@ -190,14 +190,14 @@ static void turbo_innerq_finalize(int group_size) {
190190
// Read accumulators from device
191191
float sq_accum[INNERQ_MAX_CHANNELS];
192192
int count = 0;
193-
cudaMemcpyFromSymbol(sq_accum, d_innerq_sq_accum, group_size * sizeof(float));
194-
cudaMemcpyFromSymbol(&count, d_innerq_count, sizeof(int));
193+
CUDA_CHECK(cudaMemcpyFromSymbol(sq_accum, d_innerq_sq_accum, group_size * sizeof(float)));
194+
CUDA_CHECK(cudaMemcpyFromSymbol(&count, d_innerq_count, sizeof(int)));
195195

196196
if (count <= 0) {
197197
GGML_LOG_WARN("%s: InnerQ calibration got 0 tokens, disabling\n", __func__);
198198
innerq_enabled = 0;
199199
int zero = 0;
200-
cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int));
200+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int)));
201201
return;
202202
}
203203

@@ -231,17 +231,17 @@ static void turbo_innerq_finalize(int group_size) {
231231
__func__, max_ratio);
232232
innerq_enabled = 0;
233233
int zero = 0;
234-
cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int));
234+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int)));
235235
return;
236236
}
237237

238238
// Stop calibrating, upload scales, activate
239239
int zero = 0, one = 1;
240-
cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int));
241-
cudaMemcpyToSymbol(d_innerq_scale, scale, group_size * sizeof(float));
242-
cudaMemcpyToSymbol(d_innerq_scale_inv, scale_inv, group_size * sizeof(float));
243-
cudaDeviceSynchronize(); // ensure scales are visible before activating
244-
cudaMemcpyToSymbol(d_innerq_active, &one, sizeof(int));
240+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int)));
241+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_scale, scale, group_size * sizeof(float)));
242+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_scale_inv, scale_inv, group_size * sizeof(float)));
243+
CUDA_CHECK(cudaDeviceSynchronize()); // ensure scales are visible before activating
244+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_active, &one, sizeof(int)));
245245

246246
innerq_enabled = 2; // active
247247

@@ -272,15 +272,15 @@ static void turbo_innerq_check_finalize(int group_size, int64_t ne00) {
272272
__func__, (long long)ne00, group_size);
273273
innerq_enabled = 0;
274274
int zero = 0;
275-
cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int));
275+
CUDA_CHECK(cudaMemcpyToSymbol(d_innerq_calibrating, &zero, sizeof(int)));
276276
}
277277
return;
278278
}
279279

280280
// Check if calibration is complete
281281
if (innerq_enabled == 1) {
282282
int count = 0;
283-
cudaMemcpyFromSymbol(&count, d_innerq_count, sizeof(int));
283+
CUDA_CHECK(cudaMemcpyFromSymbol(&count, d_innerq_count, sizeof(int)));
284284
if (count >= innerq_target_tokens) {
285285
turbo_innerq_finalize(group_size);
286286
}

‎tests/test-quantize-fns.cpp‎

Lines changed: 22 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -48,7 +48,10 @@ static float array_rmse(const float * a1, const float * a2, size_t n) {
4848

4949
// Total quantization error on test data
5050
static float total_quantization_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data) {
51-
std::vector<uint8_t> tmp_q(2*test_size);
51+
// Buffer must be large enough for the row's byte size. For types whose
52+
// vec_dot_type is GGML_TYPE_F32 (e.g. turbo quants), from_float writes
53+
// test_size*sizeof(float) bytes, which exceeds the legacy 2*test_size sizing.
54+
std::vector<uint8_t> tmp_q(std::max<size_t>(2*test_size, test_size * sizeof(float)));
5255
std::vector<float> tmp_out(test_size);
5356

5457
qfns_cpu->from_float(test_data, tmp_q.data(), test_size);
@@ -58,7 +61,7 @@ static float total_quantization_error(const ggml_type_traits * qfns, const ggml_
5861

5962
// Total quantization error on test data
6063
static float reference_quantization_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data) {
61-
std::vector<uint8_t> tmp_q(2*test_size);
64+
std::vector<uint8_t> tmp_q(std::max<size_t>(2*test_size, test_size * sizeof(float)));
6265
std::vector<float> tmp_out(test_size);
6366
std::vector<float> tmp_out_ref(test_size);
6467

@@ -84,8 +87,10 @@ static float dot_product(const float * a1, const float * a2, size_t test_size) {
8487
static float dot_product_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data1, const float * test_data2) {
8588
GGML_UNUSED(qfns);
8689

87-
std::vector<uint8_t> tmp_q1(2*test_size);
88-
std::vector<uint8_t> tmp_q2(2*test_size);
90+
// For turbo quants vec_dot_type is GGML_TYPE_F32, so vdot->from_float writes
91+
// test_size*sizeof(float) bytes. Size buffers accordingly.
92+
std::vector<uint8_t> tmp_q1(std::max<size_t>(2*test_size, test_size * sizeof(float)));
93+
std::vector<uint8_t> tmp_q2(std::max<size_t>(2*test_size, test_size * sizeof(float)));
8994

9095
const auto * vdot = ggml_get_type_traits_cpu(qfns_cpu->vec_dot_type);
9196

@@ -137,6 +142,16 @@ int main(int argc, char * argv[]) {
137142
continue;
138143
}
139144

145+
// TurboQuant KV-cache types (TURBO2_0/TURBO3_0/TURBO4_0) intentionally keep
146+
// their dequantized output in the WHT-rotated domain; the inverse WHT is
147+
// applied separately via GGML_OP_TURBO_WHT in the attention graph. They do
148+
// not round-trip through float space, so the total/reference/dot-product
149+
// error tests in this harness are not applicable.
150+
if (type == GGML_TYPE_TURBO2_0 || type == GGML_TYPE_TURBO3_0 || type == GGML_TYPE_TURBO4_0) {
151+
printf("Testing %s (skipped: rotated-domain KV quant)\n", ggml_type_name(type));
152+
continue;
153+
}
154+
140155
const ggml_type ei = (ggml_type)i;
141156

142157
printf("Testing %s\n", ggml_type_name((ggml_type) i));
@@ -152,6 +167,7 @@ int main(int argc, char * argv[]) {
152167
type == GGML_TYPE_Q3_K ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS :
153168
type == GGML_TYPE_IQ3_S ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS :
154169
type == GGML_TYPE_IQ3_XXS ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS_XXS :
170+
type == GGML_TYPE_TQ3_1S ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS :
155171
type == GGML_TYPE_NVFP4 ? MAX_QUANTIZATION_TOTAL_ERROR_FP4 : MAX_QUANTIZATION_TOTAL_ERROR;
156172
failed = !(total_error < max_quantization_error);
157173
num_failed += failed;
@@ -168,7 +184,8 @@ int main(int argc, char * argv[]) {
168184

169185
const float vec_dot_error = dot_product_error(qfns, qfns_cpu, test_size, test_data.data(), test_data2.data());
170186
const float max_allowed_error = type == GGML_TYPE_Q2_K || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ2_XXS ||
171-
type == GGML_TYPE_IQ3_XXS || type == GGML_TYPE_IQ3_S || type == GGML_TYPE_IQ2_S
187+
type == GGML_TYPE_IQ3_XXS || type == GGML_TYPE_IQ3_S || type == GGML_TYPE_IQ2_S ||
188+
type == GGML_TYPE_TQ3_1S
172189
? MAX_DOT_PRODUCT_ERROR_LOWBIT
173190
: type == GGML_TYPE_TQ1_0 || type == GGML_TYPE_TQ2_0
174191
? MAX_DOT_PRODUCT_ERROR_TERNARY

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