109 lines
5 KiB
MQL5
109 lines
5 KiB
MQL5
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//+------------------------------------------------------------------+
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//| KronosProfile.mq5 |
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//| MMQ — Muhammad Minhas Qamar |
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//| www.mql5.com |
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//+------------------------------------------------------------------+
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#property copyright "MMQ — Muhammad Minhas Qamar"
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#property link "https://www.mql5.com"
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#property version "1.00"
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#property script_show_inputs
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#property strict
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#include <Kronos\KronosInference.mqh>
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//--- tokenizer config (config_tokenizer.json)
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#define KR_TOK_DIR "kronos_weights\\tokenizer\\"
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#define KR_TOK_DM 256
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#define KR_TOK_HEADS 4
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#define KR_TOK_ENC 4
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#define KR_TOK_DEC 4
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#define KR_TOK_FF 512
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//--- predictor config (config_predictor.json)
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#define KR_PRED_DIR "kronos_weights\\predictor\\"
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#define KR_PRED_DM 512
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#define KR_PRED_HEADS 8
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#define KR_PRED_LAYERS 8
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#define KR_PRED_FF 1024
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//--- real config, matching KronosForecast.mq5 defaults
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input string InpRefDir = "kronos_refs\\";
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input int InpLookback = 256; // context bars
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input int InpPredLen = 16; // forecast horizon
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input double InpTemperature = 1.0; // sampling temperature
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input int InpTopK = 0; // top-k (0 = off)
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input double InpTopP = 0.9; // nucleus top-p
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input int InpSampleCount = 5; // averaged sample paths (the EA default)
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input bool InpGreedy = false; // EA runs stochastic; profile the real cost
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//+------------------------------------------------------------------+
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//| Read a [rows,cols] float32 .bin into a matrix(double). |
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//+------------------------------------------------------------------+
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bool LoadF32Matrix(const string fname, ulong rows, ulong cols, matrix &out)
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{
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int h = FileOpen(fname, FILE_READ | FILE_BIN);
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if(h == INVALID_HANDLE)
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{ PrintFormat("open fail %s (%d)", fname, GetLastError()); return false; }
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ulong n = rows * cols;
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float buf[];
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ArrayResize(buf, (int)n);
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uint got = FileReadArray(h, buf, 0, (int)n);
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FileClose(h);
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if(got != n)
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{ PrintFormat("short read %s", fname); return false; }
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out = matrix::Zeros(rows, cols);
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for(ulong r = 0; r < rows; r++)
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for(ulong c = 0; c < cols; c++)
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out[r][c] = (double)buf[r*cols+c];
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return true;
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}
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//+------------------------------------------------------------------+
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//| Script entry point: one full Predict(), timed, then exit. |
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//+------------------------------------------------------------------+
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void OnStart()
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{
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const int L = InpLookback, P = InpPredLen;
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Print("============ Kronos profile (one full Predict, real config) ============");
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PrintFormat("config: L=%d pred_len=%d sample_count=%d greedy=%s topP=%.2f",
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L, P, InpSampleCount, (InpGreedy ? "true" : "false"), InpTopP);
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if(L > 256)
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{ Print("lookback>256 not available from refs"); return; }
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//--- reference window (already normalized) reused as Predict's raw input; Predict
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//--- re-normalizes internally — fine for profiling (compute path is value-agnostic)
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matrix raw, x_stamp, y_stamp;
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if(!LoadF32Matrix(InpRefDir + "x_norm.bin", (ulong)L, KR_NFEAT, raw)) { Print("ABORT x_norm"); return; }
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if(!LoadF32Matrix(InpRefDir + "x_stamp.bin", (ulong)L, 5, x_stamp)) { Print("ABORT x_stamp"); return; }
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if(!LoadF32Matrix(InpRefDir + "y_stamp.bin", (ulong)P, 5, y_stamp)) { Print("ABORT y_stamp"); return; }
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matrix full_stamp = matrix::Zeros((ulong)(L + P), 5);
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for(int i = 0; i < L; i++)
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for(int j = 0; j < 5; j++)
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full_stamp[i][j] = x_stamp[i][j];
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for(int i = 0; i < P; i++)
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for(int j = 0; j < 5; j++)
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full_stamp[L + i][j] = y_stamp[i][j];
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CKronosModel model;
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uint t0 = GetTickCount();
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if(!model.Init(KR_TOK_DIR, KR_TOK_ENC, KR_TOK_DEC, KR_TOK_DM, KR_TOK_HEADS, KR_TOK_FF,
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KR_PRED_DIR, KR_PRED_LAYERS, KR_PRED_DM, KR_PRED_HEADS, KR_PRED_FF, 512))
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{ Print("ABORT: model Init failed"); return; }
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PrintFormat("weight load: %u ms", GetTickCount() - t0);
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//--- the exact call KronosForecast.mq5 makes, once
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uint t1 = GetTickCount();
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matrix forecast;
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if(!model.Predict(raw, full_stamp, P, InpTemperature, InpTopK, InpTopP,
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InpSampleCount, InpGreedy, forecast))
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{ Print("ABORT: Predict failed"); return; }
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uint dt = GetTickCount() - t1;
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PrintFormat("Predict (L=%d, P=%d, samples=%d): %u ms total -> ~%.1f ms/step/path",
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L, P, InpSampleCount, dt, (double)dt / (P * InpSampleCount));
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PrintFormat("forecast rows=%I64u cols=%I64u, first close=%.5f last close=%.5f",
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forecast.Rows(), forecast.Cols(), forecast[0][3], forecast[P - 1][3]);
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Print("=========================================================================");
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}
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//+------------------------------------------------------------------+
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