Nik Afiq
5238298b55
- Implemented core model components in `modules.py` including various convolutional layers and normalization techniques. - Added transformation functions in `transforms.py` for piecewise rational quadratic transformations. - Created utility functions in `utils.py` for checkpoint management, logging, and hyperparameter handling. - Introduced monotonic alignment functionality with Cython optimization in `monotonic_align`. - Developed a minimal inference server in `server.py` to handle synthesis requests. - Updated requirements to include necessary dependencies for Cython and scipy.
97 lines
3.0 KiB
Go
97 lines
3.0 KiB
Go
// Package inferencesidecar implements driven.TTSEngine by calling a small
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// Python/libtorch sidecar (tts-gateway/sidecar) over HTTP - the fallback
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// documented in TTS_GATEWAY_PLAN.md's Risk 1 and adopted after the Phase 0
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// spike found the checkpoint's data-dependent output length isn't cleanly
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// exportable via torch.export. Same shape as ai-gateway's Ollama client:
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// the tensor math lives outside Go, hidden behind this port like any other
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// outbound dependency.
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package inferencesidecar
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import (
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"bytes"
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"context"
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"encoding/binary"
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"encoding/json"
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"fmt"
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"io"
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"math"
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"net/http"
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"strconv"
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"time"
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"gitea.nik4nao.com/nik/home-services/tts-gateway/internal/core/domain"
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)
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type Client struct {
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baseURL string
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httpClient *http.Client
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}
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// NewClient constructs the sidecar HTTP client. addr is a host:port, e.g.
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// "localhost:50054" (config.Config.InferenceSidecarAddr).
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func NewClient(addr string) *Client {
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return &Client{
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baseURL: "http://" + addr,
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httpClient: &http.Client{Timeout: 60 * time.Second},
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}
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}
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type synthesizeRequest struct {
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SpeakerID int `json:"speaker_id"`
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SymbolIDs []int64 `json:"symbol_ids"`
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NoiseScale float32 `json:"noise_scale"`
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NoiseScaleW float32 `json:"noise_scale_w"`
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LengthScale float32 `json:"length_scale"`
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}
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// Synthesize posts symbol IDs + params to the sidecar's /synthesize
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// endpoint and decodes its raw little-endian float32 PCM response.
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func (c *Client) Synthesize(ctx context.Context, speakerID int, symbolIDs []int64, params domain.SynthesisParams) ([]float32, int, error) {
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reqBody, err := json.Marshal(synthesizeRequest{
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SpeakerID: speakerID,
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SymbolIDs: symbolIDs,
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NoiseScale: params.NoiseScale,
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NoiseScaleW: params.NoiseScaleW,
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LengthScale: params.LengthScale,
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})
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if err != nil {
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return nil, 0, fmt.Errorf("inferencesidecar: marshal request: %w", err)
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}
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req, err := http.NewRequestWithContext(ctx, http.MethodPost, c.baseURL+"/synthesize", bytes.NewReader(reqBody))
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if err != nil {
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return nil, 0, fmt.Errorf("inferencesidecar: build request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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resp, err := c.httpClient.Do(req)
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if err != nil {
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return nil, 0, fmt.Errorf("inferencesidecar: request failed: %w", err)
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}
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defer resp.Body.Close()
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data, err := io.ReadAll(resp.Body)
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if err != nil {
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return nil, 0, fmt.Errorf("inferencesidecar: read response: %w", err)
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}
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if resp.StatusCode != http.StatusOK {
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return nil, 0, fmt.Errorf("inferencesidecar: %s: %s", resp.Status, string(data))
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}
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sampleRate, err := strconv.Atoi(resp.Header.Get("X-Sample-Rate"))
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if err != nil {
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return nil, 0, fmt.Errorf("inferencesidecar: missing/invalid X-Sample-Rate header: %w", err)
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}
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if len(data)%4 != 0 {
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return nil, 0, fmt.Errorf("inferencesidecar: response length %d not a multiple of 4", len(data))
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}
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pcm := make([]float32, len(data)/4)
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for i := range pcm {
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bits := binary.LittleEndian.Uint32(data[i*4 : i*4+4])
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pcm[i] = math.Float32frombits(bits)
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}
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return pcm, sampleRate, nil
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}
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