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.
39 lines
1013 B
Go
39 lines
1013 B
Go
package logger
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import (
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"context"
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"fmt"
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"log/slog"
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"os"
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)
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type contextKey struct{}
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// New constructs a root logger for the configured format and level.
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func New(format, level string) *slog.Logger {
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var parsed slog.Level
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if err := parsed.UnmarshalText([]byte(level)); err != nil {
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_, _ = fmt.Fprintf(os.Stderr, "invalid log level %q, falling back to info\n", level)
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parsed = slog.LevelInfo
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}
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opts := &slog.HandlerOptions{Level: parsed}
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if format == "json" {
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return slog.New(slog.NewJSONHandler(os.Stdout, opts))
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}
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return slog.New(slog.NewTextHandler(os.Stdout, opts))
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}
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// WithLogger attaches a logger to the provided context.
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func WithLogger(ctx context.Context, l *slog.Logger) context.Context {
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return context.WithValue(ctx, contextKey{}, l)
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}
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// FromContext retrieves a logger from context and falls back to slog.Default().
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func FromContext(ctx context.Context) *slog.Logger {
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if l, ok := ctx.Value(contextKey{}).(*slog.Logger); ok && l != nil {
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return l
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}
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return slog.Default()
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}
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