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@@ -10828,6 +10828,7 @@ static void delta_tensor_add_chunk_f32(const float * a, const float * b, float *
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static void print_debug_info(float * data, size_t size, const char * name, int64_t token) {
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+#ifdef LOGS_OF_DEBUGS
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GGML_LOG_INFO("\nggml-debug: %s (%ld) first 5 values: [%.6f, %.6f, %.6f, %.6f, %.6f, ...]\n",
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name, token, data[0], data[1], data[2], data[3], data[4]);
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double sum = 0.0;
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@@ -10835,6 +10836,7 @@ static void print_debug_info(float * data, size_t size, const char * name, int64
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sum += data[i];
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}
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GGML_LOG_INFO("total elements: %ld, sum = %.10f\n", size, sum);
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+#endif
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}
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void ggml_compute_forward_delta_net_f32(const ggml_compute_params * params, ggml_tensor * dst) {
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@@ -11209,18 +11211,18 @@ void ggml_compute_forward_delta_net_f32(const ggml_compute_params * params, ggml
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}
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}
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print_debug_info(output, S_v * H_v * n_tokens * n_seqs, "output", chunk);
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- GGML_LOG_INFO("\nFull output tensor: \n\n");
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- for (int64_t seq = 0; seq < n_seqs; seq++) {
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- for (int64_t head = 0; head < H_v; head++) {
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- GGML_LOG_INFO("\n[ ");
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- for (int64_t i = 0; i < n_tokens; i++) {
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- for (int64_t d = 0; d < S_v; d++) {
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- GGML_LOG_INFO("%.4f ", output[seq * (n_tokens * S_v * H_v) + head * (n_tokens * S_v) + (chunk * chunk_size + i) * S_v + d]);
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- }
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- }
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- GGML_LOG_INFO(" ]");
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- }
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- }
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+ // GGML_LOG_INFO("\nFull output tensor: \n\n");
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+ // for (int64_t seq = 0; seq < n_seqs; seq++) {
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+ // for (int64_t head = 0; head < H_v; head++) {
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+ // GGML_LOG_INFO("\n[ ");
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+ // for (int64_t i = 0; i < n_tokens; i++) {
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+ // for (int64_t d = 0; d < S_v; d++) {
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+ // GGML_LOG_INFO("%.4f ", output[seq * (n_tokens * S_v * H_v) + head * (n_tokens * S_v) + (chunk * chunk_size + i) * S_v + d]);
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+ // }
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+ // }
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+ // GGML_LOG_INFO(" ]");
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+ // }
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+ // }
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print_debug_info(new_state, S_v * S_v * H_v * n_seqs, "new_state", chunk);
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free(temp_state);
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