parent
eab788aabd
commit
194277297f
@ -86,6 +86,8 @@ func handleDelete(handle *Handle) {
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case FAILED_PREPARING:
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deleteModel(handle, id, w, c, model)
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return nil
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case READY:
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fallthrough
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case CONFIRM_PRE_TRAINING:
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if CheckEmpty(f, "name") {
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@ -69,7 +69,6 @@ func handleEdit(handle *Handle) {
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"Model": model,
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}))
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case CONFIRM_PRE_TRAINING:
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cls, err := model_classes.ListClasses(handle.Db, id)
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if err != nil {
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return Error500(err)
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@ -85,6 +84,10 @@ func handleEdit(handle *Handle) {
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"Classes": cls,
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"HasData": has_data,
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}))
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case READY:
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LoadBasedOnAnswer(c.Mode, w, "/models/edit.html", c.AddMap(AnyMap{
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"Model": model,
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}))
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case TRAINING:
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fallthrough
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case PREPARING_ZIP_FILE:
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118
logic/models/run.go
Normal file
118
logic/models/run.go
Normal file
@ -0,0 +1,118 @@
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package models
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import (
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"bytes"
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"fmt"
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"io"
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"net/http"
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"os"
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"path"
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. "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/utils"
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. "git.andr3h3nriqu3s.com/andr3/fyp/logic/utils"
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tf "github.com/galeone/tensorflow/tensorflow/go"
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tg "github.com/galeone/tfgo"
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"github.com/galeone/tfgo/image"
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)
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func handleRun(handle *Handle) {
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handle.Post("/models/run", func(w http.ResponseWriter, r *http.Request, c *Context) *Error {
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if !CheckAuthLevel(1, w, r, c) {
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return nil
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}
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if c.Mode == JSON {
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// TODO improve message
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return ErrorCode(nil, 400, nil)
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}
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read_form, err := r.MultipartReader()
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if err != nil {
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// TODO improve message
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return ErrorCode(nil, 400, nil)
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}
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var id string
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var file []byte
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for {
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part, err_part := read_form.NextPart()
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if err_part == io.EOF {
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break
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} else if err_part != nil {
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return &Error{Code: http.StatusBadRequest}
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}
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if part.FormName() == "id" {
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buf := new(bytes.Buffer)
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buf.ReadFrom(part)
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id = buf.String()
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}
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if part.FormName() == "file" {
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buf := new(bytes.Buffer)
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buf.ReadFrom(part)
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file = buf.Bytes()
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}
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}
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model, err := GetBaseModel(handle.Db, id)
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if err == ModelNotFoundError {
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return ErrorCode(nil, http.StatusNotFound, AnyMap{
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"NotFoundMessage": "Model not found",
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"GoBackLink": "/models",
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})
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} else if err != nil {
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return Error500(err)
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}
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if model.Status != READY {
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// TODO improve this
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return ErrorCode(nil, 400, c.AddMap(nil))
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}
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definitions_rows, err := handle.Db.Query("select id from model_definition where model_id=$1;", model.Id)
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if !definitions_rows.Next() {
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// TODO improve this
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return ErrorCode(nil, 400, c.AddMap(nil))
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}
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defer definitions_rows.Close()
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if !definitions_rows.Next() {
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return Error500(nil)
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}
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var def_id string
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if err = definitions_rows.Scan(&def_id); err != nil {
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return Error500(nil)
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}
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// TODO create a database table with tasks
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run_path := path.Join("/tmp", model.Id, "runs")
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os.MkdirAll(run_path, os.ModePerm)
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img_file, err := os.Create(path.Join(run_path, "img.png"))
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if err != nil {
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return Error500(nil)
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}
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defer img_file.Close()
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img_file.Write(file)
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root := tg.NewRoot()
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tf_img := image.Read(root, path.Join(run_path, "img.png"), 1)
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tf_model := tg.LoadModel(path.Join("savedData", model.Id, "defs", def_id, "model"), []string{"serve"}, nil)
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tf_img_tensor, err := tf.NewTensor(tf_img.Value())
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if err != nil {
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return Error500(err)
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}
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results := tf_model.Exec([]tf.Output{
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tf_model.Op("StatefulPartitionedCall", 0),
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}, map[tf.Output]*tf.Tensor{
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tf_model.Op("serving_default_inputs_input", 0): tf_img_tensor,
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})
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predictions := results[0]
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fmt.Println(predictions.Value())
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return nil
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})
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}
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@ -2,6 +2,8 @@ package models_train
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import (
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"net/http"
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"os"
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"path"
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. "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/utils"
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. "git.andr3h3nriqu3s.com/andr3/fyp/logic/utils"
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@ -40,11 +42,13 @@ func handleRest(handle *Handle) {
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return Error500(err)
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}
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if model.Status != FAILED_PREPARING_TRAINING {
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if model.Status != FAILED_PREPARING_TRAINING && model.Status != FAILED_TRAINING {
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// TODO improve response
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return ErrorCode(nil, 400, c.AddMap(nil))
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}
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os.RemoveAll(path.Join("savedData", model.Id, "defs"))
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_, err = handle.Db.Exec("delete from model_definition where model_id=$1", model.Id)
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if err != nil {
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// TODO improve response
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@ -4,7 +4,13 @@ import (
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"database/sql"
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"errors"
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"fmt"
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"io"
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"net/http"
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"os"
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"os/exec"
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"path"
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"strconv"
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"text/template"
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model_classes "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/classes"
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. "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/utils"
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@ -47,18 +53,117 @@ const (
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MODEL_DEFINITION_STATUS_READY = 5
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)
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type LayerType int
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const (
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LAYER_INPUT LayerType = 1
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LAYER_DENSE = 2
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LAYER_FLATTEN = 3
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)
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func ModelDefinitionUpdateStatus(handle *Handle, id string, status ModelDefinitionStatus) (err error) {
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_, err = handle.Db.Exec("update model_definition set status = $1 where id = $2", status, id)
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return
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}
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func MakeLayer(db *sql.DB, def_id string, layer_order int, layer_type int, shape string) (err error) {
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func MakeLayer(db *sql.DB, def_id string, layer_order int, layer_type LayerType, shape string) (err error) {
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_, err = db.Exec("insert into model_definition_layer (def_id, layer_order, layer_type, shape) values ($1, $2, $3, $4)", def_id, layer_order, layer_type, shape)
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return
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}
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func trainDefinition(handle *Handle, model_id string, definition_id string) (accuracy float64, err error) {
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accuracy = 0
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layers, err := handle.Db.Query("select layer_type, shape from model_definition_layer where def_id=$1 order by layer_order asc;", definition_id)
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if err != nil {
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return
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}
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defer layers.Close()
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type layerrow struct {
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LayerType int
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Shape string
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}
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got := []layerrow{}
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for layers.Next() {
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var row = layerrow{}
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if err = layers.Scan(&row.LayerType, &row.Shape); err != nil {
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return
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}
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row.Shape = shapeToSize(row.Shape)
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got = append(got, row)
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}
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// Generate run folder
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run_path := path.Join("/tmp", model_id, "defs", definition_id)
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err = os.MkdirAll(run_path, os.ModePerm)
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if err != nil {
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return
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}
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// Create python script
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f, err := os.Create(path.Join(run_path, "run.py"))
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if err != nil {
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return
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}
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defer f.Close()
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tmpl, err := template.New("python_model_template.py").ParseFiles("views/py/python_model_template.py")
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if err != nil {
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return
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}
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if err = tmpl.Execute(f, AnyMap{
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"Layers": got,
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"Size": got[0].Shape,
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"DataDir": path.Join(getDir(), "savedData", model_id, "data", "training"),
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}); err != nil {
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return
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}
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// Run the command
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if err = exec.Command("bash", "-c", fmt.Sprintf("cd %s && python run.py", run_path)).Run(); err != nil {
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return
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}
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// Copy result around
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result_path := path.Join("savedData", model_id, "defs", definition_id)
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if err = os.MkdirAll(result_path, os.ModePerm); err != nil {
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return
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}
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if err = exec.Command("cp", "-r", path.Join(run_path, "model"), path.Join(result_path, "model")).Run(); err != nil {
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return
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}
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accuracy_file, err := os.Open(path.Join(run_path, "accuracy.val"))
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if err != nil {
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return
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}
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defer accuracy_file.Close()
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accuracy_file_bytes, err := io.ReadAll(accuracy_file)
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if err != nil {
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return
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}
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fmt.Println(string(accuracy_file_bytes))
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accuracy, err = strconv.ParseFloat(string(accuracy_file_bytes), 64)
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if err != nil {
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return
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}
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os.RemoveAll(run_path)
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return
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}
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func trainModel(handle *Handle, model *BaseModel) {
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definitionsRows, err := handle.Db.Query("select id from model_definition where status=$1 and model_id=$2", MODEL_DEFINITION_STATUS_INIT)
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definitionsRows, err := handle.Db.Query("select id, target_accuracy from model_definition where status=$1 and model_id=$2", MODEL_DEFINITION_STATUS_INIT, model.Id)
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if err != nil {
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fmt.Printf("Failed to trainModel!Err:\n")
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fmt.Println(err)
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@ -67,17 +172,22 @@ func trainModel(handle *Handle, model *BaseModel) {
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}
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defer definitionsRows.Close()
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definitions := []string{}
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type row struct {
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id string
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target_accuracy int
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}
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definitions := []row{}
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for definitionsRows.Next() {
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var id string
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if err = definitionsRows.Scan(&id); err != nil {
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var rowv row
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if err = definitionsRows.Scan(&rowv.id, &rowv.target_accuracy); err != nil {
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fmt.Printf("Failed to trainModel!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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definitions = append(definitions, id)
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definitions = append(definitions, rowv)
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}
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if len(definitions) == 0 {
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@ -87,9 +197,91 @@ func trainModel(handle *Handle, model *BaseModel) {
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return
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}
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for _, def_id := range definitions {
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_ = def_id
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for _, def := range definitions {
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accuracy, err := trainDefinition(handle, model.Id, def.id)
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if err != nil {
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fmt.Printf("Failed to train definition!Err:\n")
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fmt.Println(err)
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ModelDefinitionUpdateStatus(handle, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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continue
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}
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int_accuracy := int(accuracy * 100)
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if int_accuracy < def.target_accuracy {
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fmt.Printf("Failed to train definition! Accuracy less %d < %d\n", int_accuracy, def.target_accuracy)
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ModelDefinitionUpdateStatus(handle, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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continue
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}
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_, err = handle.Db.Exec("update model_definition set accuracy=$1, status=$2 where id=$3", int_accuracy, MODEL_DEFINITION_STATUS_TRANIED, def.id)
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if err != nil {
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fmt.Printf("Failed to train definition!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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}
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rows, err := handle.Db.Query("select id from model_definition where model_id=$1 and status=$2 order by accuracy desc limit 1;", model.Id, MODEL_DEFINITION_STATUS_TRANIED)
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if err != nil {
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fmt.Printf("Db err select!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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defer rows.Close()
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if !rows.Next() {
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// TODO improve message
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fmt.Printf("All definitions failed to train!")
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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var id string
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if err = rows.Scan(&id); err != nil {
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fmt.Printf("Db err!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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if _, err = handle.Db.Exec("update model_definition set status=$1 where id=$2;", MODEL_DEFINITION_STATUS_READY, id); err != nil {
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fmt.Printf("Db err!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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to_delete, err := handle.Db.Query("select id from model_definition where status != $1 and model_id=$2", MODEL_DEFINITION_STATUS_READY, model.Id)
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if err != nil {
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fmt.Printf("Db err!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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defer to_delete.Close()
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for to_delete.Next() {
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var id string
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if to_delete.Scan(&id);err != nil {
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fmt.Printf("Db err!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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os.RemoveAll(path.Join("savedData", model.Id, "defs", id))
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}
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if _, err = handle.Db.Exec("delete from model_definition where status!=$1 and model_id=$2;", MODEL_DEFINITION_STATUS_READY, model.Id); err != nil {
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fmt.Printf("Db err!Err:\n")
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fmt.Println(err)
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ModelUpdateStatus(handle, model.Id, FAILED_TRAINING)
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return
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}
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ModelUpdateStatus(handle, model.Id, READY)
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}
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func handleTrain(handle *Handle) {
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@ -120,6 +312,24 @@ func handleTrain(handle *Handle) {
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// Its not used rn
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_ = model_type
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// TODO check if the model has data
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/*rows, err := handle.Db.Query("select mc.name, mdp.file_path from model_classes as mc join model_data_point as mdp on mdp.class_id = mc.id where mdp.model_mode = 1 and mc.model_id = $1 limit 1;", id)
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if err != nil {
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return Error500(err)
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}
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defer rows.Close()
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if !rows.Next() {
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return Error500(err)
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}
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var name string
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var file_path string
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err = rows.Scan(&name, &file_path)
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if err != nil {
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return Error500(err)
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}*/
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model, err := GetBaseModel(handle.Db, id)
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if err == ModelNotFoundError {
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return ErrorCode(nil, http.StatusNotFound, c.AddMap(AnyMap{
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@ -143,7 +353,6 @@ func handleTrain(handle *Handle) {
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return Error500(err)
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}
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|
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var fid string
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for i := 0; i < number_of_models; i++ {
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def_id, err := MakeDefenition(handle.Db, model.Id, accuracy)
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@ -158,19 +367,25 @@ func handleTrain(handle *Handle) {
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}
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// TODO change shape of it depends on the type of the image
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err = MakeLayer(handle.Db, def_id, 1, 1, fmt.Sprintf("%d,%d,1", model.Width, model.Height))
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err = MakeLayer(handle.Db, def_id, 1, LAYER_INPUT, fmt.Sprintf("%d,%d,1", model.Width, model.Height))
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if err != nil {
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ModelUpdateStatus(handle, model.Id, FAILED_PREPARING_TRAINING)
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// TODO improve this response
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return Error500(err)
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}
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err = MakeLayer(handle.Db, def_id, 4, 3, fmt.Sprintf("%d,1", len(cls)))
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err = MakeLayer(handle.Db, def_id, 4, LAYER_FLATTEN, fmt.Sprintf("%d,1", len(cls)))
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if err != nil {
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ModelUpdateStatus(handle, model.Id, FAILED_PREPARING_TRAINING)
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// TODO improve this response
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return Error500(err)
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}
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err = MakeLayer(handle.Db, def_id, 5, 2, fmt.Sprintf("%d,1", len(cls)))
|
||||
err = MakeLayer(handle.Db, def_id, 5, LAYER_DENSE, fmt.Sprintf("%d,1", len(cls) * 3))
|
||||
if err != nil {
|
||||
ModelUpdateStatus(handle, model.Id, FAILED_PREPARING_TRAINING)
|
||||
// TODO improve this response
|
||||
return Error500(err)
|
||||
}
|
||||
err = MakeLayer(handle.Db, def_id, 5, LAYER_DENSE, fmt.Sprintf("%d,1", len(cls)))
|
||||
if err != nil {
|
||||
ModelUpdateStatus(handle, model.Id, FAILED_PREPARING_TRAINING)
|
||||
// TODO improve this response
|
||||
|
@ -24,6 +24,7 @@ const (
|
||||
CONFIRM_PRE_TRAINING = 2
|
||||
PREPARING_ZIP_FILE = 3
|
||||
TRAINING = 4
|
||||
READY = 5
|
||||
)
|
||||
|
||||
var ModelNotFoundError = errors.New("Model not found error")
|
||||
|
@ -468,7 +468,7 @@ func (x Handle) ReadFiles(pathTest string, baseFilePath string, fileType string,
|
||||
http.HandleFunc(pathTest, func(w http.ResponseWriter, r *http.Request) {
|
||||
user_path := r.URL.Path[len(pathTest):]
|
||||
|
||||
fmt.Printf("Requested path: %s\n", user_path)
|
||||
// fmt.Printf("Requested path: %s\n", user_path)
|
||||
|
||||
if !strings.HasSuffix(user_path, fileType) {
|
||||
w.WriteHeader(http.StatusNotFound)
|
||||
|
@ -288,6 +288,30 @@
|
||||
</form>
|
||||
{{ end }}
|
||||
|
||||
{{ define "run-model-card" }}
|
||||
<form hx-headers='{"REQUEST-TYPE": "html"}' enctype="multipart/form-data" hx-post="/models/run">
|
||||
<input type="hidden" name="id" value={{.Model.Id}} />
|
||||
<fieldset class="file-upload" >
|
||||
<label for="file">Image</label>
|
||||
<div class="form-msg">
|
||||
Run image through them model and get the result
|
||||
</div>
|
||||
<div class="icon-holder">
|
||||
<button class="icon">
|
||||
<img replace="icon" src="/imgs/upload-icon.png" />
|
||||
<span replace="File Selected">
|
||||
Image File
|
||||
</span>
|
||||
</button>
|
||||
<input id="file" name="file" type="file" required accept="application/zip" />
|
||||
</div>
|
||||
</fieldset>
|
||||
<button>
|
||||
Run
|
||||
</button>
|
||||
</form>
|
||||
{{ end }}
|
||||
|
||||
{{ define "mainbody" }}
|
||||
<main>
|
||||
{{ if (eq .Model.Status 1) }}
|
||||
@ -345,7 +369,7 @@
|
||||
Processing zip file...
|
||||
</div>
|
||||
{{/* FAILED TO Prepare for training */}}
|
||||
{{ else if (eq .Model.Status -3)}}
|
||||
{{ else if or (eq .Model.Status -3) (eq .Model.Status -4)}}
|
||||
{{ template "base-model-card" . }}
|
||||
<form hx-delete="/models/train/reset" hx-headers='{"REQUEST-TYPE": "html"}' hx-swap="outerHTML">
|
||||
Failed Prepare for training.<br/>
|
||||
@ -364,9 +388,11 @@
|
||||
{{/* TODO Add progress status on definitions */}}
|
||||
{{/* TODO Add aility to stop training */}}
|
||||
</div>
|
||||
<button hx-post="/models/train/test?id={{ .Model.Id }}" hx-headers='{"REQUEST-TYPE": "html"}'>
|
||||
Test
|
||||
</button>
|
||||
{{/* Model Ready */}}
|
||||
{{ else if (eq .Model.Status 5)}}
|
||||
{{ template "base-model-card" . }}
|
||||
{{ template "run-model-card" . }}
|
||||
{{ template "delete-model-card" . }}
|
||||
{{ else }}
|
||||
<h1>
|
||||
Unknown Status of the model.
|
||||
|
@ -46,7 +46,7 @@ model.compile(
|
||||
optimizer=tf.keras.optimizers.Adam(),
|
||||
metrics=['accuracy'])
|
||||
|
||||
his = model.fit(dataset, validation_data= dataset_validation, epochs=50)
|
||||
his = model.fit(dataset, validation_data= dataset_validation, epochs=70)
|
||||
|
||||
acc = his.history["accuracy"]
|
||||
|
||||
@ -54,4 +54,6 @@ f = open("accuracy.val", "w")
|
||||
f.write(str(acc[-1]))
|
||||
f.close()
|
||||
|
||||
model.save("model.keras")
|
||||
tf.saved_model.save(model, "model")
|
||||
|
||||
# model.save("model.keras", save_format="tf")
|
||||
|
Loading…
Reference in New Issue
Block a user