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ggml : fix cont with transposed tensors when one dimension is 1 (ggml/934)
* ggml_cont: fix issue with transposed tensors when one dimension is 1 when using multiple threads, it is not enough to check for the tensors to be contiguous for ggml_compute_forward_dup_same_cont to work correctly. The tensors strides also need to match. Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com> * Add ggml_cont tests Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com> * Remove dead code it isn't possible to reach this code because all these functions are invoked by ggml_compute_forward_dup if and only if src0->type != dst->type Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com> * Make ggml_compute_forward_dup_same_cont work with contiguous tensors Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com> --------- Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -8322,8 +8322,7 @@ static void ggml_compute_forward_dup_same_cont(
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GGML_ASSERT(ggml_is_contiguous(dst) && ggml_is_contiguous(src0));
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GGML_ASSERT(src0->type == dst->type);
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const size_t nb00 = src0->nb[0];
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const size_t nb0 = dst->nb[0];
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const size_t nb0 = ggml_type_size(src0->type);
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const int ith = params->ith; // thread index
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const int nth = params->nth; // number of threads
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@ -8337,8 +8336,8 @@ static void ggml_compute_forward_dup_same_cont(
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if (ie0 < ie1) {
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memcpy(
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((char *) dst->data + ie0*nb0),
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((char *) src0->data + ie0*nb00),
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(ie1 - ie0) * ggml_type_size(src0->type));
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((char *) src0->data + ie0*nb0),
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(ie1 - ie0) * nb0);
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}
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}
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@ -8355,11 +8354,6 @@ static void ggml_compute_forward_dup_f16(
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const int ith = params->ith; // thread index
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const int nth = params->nth; // number of threads
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if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst) && src0->type == dst->type) {
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ggml_compute_forward_dup_same_cont(params, dst);
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return;
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}
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// parallelize by rows
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const int nr = ne01;
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// number of rows per thread
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@ -8624,11 +8618,6 @@ static void ggml_compute_forward_dup_bf16(
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const int ith = params->ith; // thread index
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const int nth = params->nth; // number of threads
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if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst) && src0->type == dst->type) {
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ggml_compute_forward_dup_same_cont(params, dst);
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return;
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}
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// parallelize by rows
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const int nr = ne01;
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// number of rows per thread
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@ -8980,11 +8969,6 @@ static void ggml_compute_forward_dup_f32(
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const int ith = params->ith; // thread index
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const int nth = params->nth; // number of threads
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if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst) && src0->type == dst->type) {
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ggml_compute_forward_dup_same_cont(params, dst);
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return;
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}
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// parallelize by rows
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const int nr = ne01;
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// number of rows per thread
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@ -9294,13 +9278,13 @@ static void ggml_compute_forward_dup_bytes(
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GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0));
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GGML_ASSERT(src0->type == dst->type);
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GGML_TENSOR_UNARY_OP_LOCALS;
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if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst)) {
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ggml_compute_forward_dup_same_cont(params, dst);
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return;
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}
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GGML_TENSOR_UNARY_OP_LOCALS;
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const size_t type_size = ggml_type_size(src0->type);
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const int ith = params->ith; // thread index
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const int nth = params->nth; // number of threads
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@ -2322,6 +2322,15 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
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}
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test_cases.emplace_back(new test_cont());
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test_cases.emplace_back(new test_cont(GGML_TYPE_F32, {2, 1, 1 ,1}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_F32, {2, 1, 3 ,5}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_F32, {2, 3, 5 ,7}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_F16, {2, 1, 1 ,1}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_F16, {2, 1, 3 ,5}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_F16, {2, 3, 5 ,7}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_BF16, {2, 1, 1 ,1}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_BF16, {2, 1, 3 ,5}));
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test_cases.emplace_back(new test_cont(GGML_TYPE_BF16, {2, 3, 5 ,7}));
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auto add_test_bin_bcast = [&](ggml_type type, std::array<int64_t, 4> ne, std::array<int, 4> nr) {
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for (auto op : {ggml_add, ggml_mul, ggml_div}) {
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