diff --git a/myproject/docker-compose.yml b/myproject/docker-compose.yml
index 646ed6edf7373383aaeadede99e06f9863a8b147..976121da56f2d023d43a325fd7948e21340ea351 100644
--- a/myproject/docker-compose.yml
+++ b/myproject/docker-compose.yml
@@ -19,6 +19,7 @@ services:
volumes:
- .:/usr/src/app
- static_volume:/usr/src/app/static
+ - ./models:/usr/src/app/models
depends_on:
- db
- tensorflow_serving
diff --git a/myproject/models/instrument_model/1/fingerprint.pb b/myproject/models/instrument_model/1/fingerprint.pb
deleted file mode 100644
index 141b4c1792009ca22145b9f5ba9c01ed66ce207c..0000000000000000000000000000000000000000
--- a/myproject/models/instrument_model/1/fingerprint.pb
+++ /dev/null
@@ -1 +0,0 @@
-؋���������ס�ȭ��ʏ����� �Ԛ���ʘ�(����Ǜ 2
\ No newline at end of file
diff --git a/myproject/models/instrument_model/1/keras_metadata.pb b/myproject/models/instrument_model/1/keras_metadata.pb
index 4d889d7af020adb530b97500ddd438adb64c68a7..17c52e5f3ac95836f44215e4d16ccc8403689e22 100644
--- a/myproject/models/instrument_model/1/keras_metadata.pb
+++ b/myproject/models/instrument_model/1/keras_metadata.pb
@@ -1,7 +1,7 @@
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"bias_constraint": null}, "shared_object_id": 17}, {"class_name": "Dropout", "config": {"name": "dropout_2", "trainable": true, "dtype": "float32", "rate": 0.2, "noise_shape": null, "seed": null}, "shared_object_id": 18}, {"class_name": "Dense", "config": {"name": "dense_1", "trainable": true, "dtype": "float32", "units": 32, "activation": "relu", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 19}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 20}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 21}, {"class_name": "Dense", "config": {"name": "dense_2", "trainable": true, "dtype": "float32", "units": 4, "activation": "softmax", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 22}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 23}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 24}]}}, "training_config": {"loss": {"class_name": "SparseCategoricalCrossentropy", "config": {"reduction": "auto", "name": "sparse_categorical_crossentropy", "from_logits": true, "ignore_class": null}, "shared_object_id": 27}, "metrics": [[{"class_name": "MeanMetricWrapper", "config": {"name": "accuracy", "dtype": "float32", "fn": "sparse_categorical_accuracy"}, "shared_object_id": 28}]], "weighted_metrics": null, "loss_weights": null, "optimizer_config": {"class_name": "Adam", "config": {"name": "Adam", "learning_rate": 0.0010000000474974513, "decay": 0.0, "beta_1": 0.8999999761581421, "beta_2": 0.9990000128746033, "epsilon": 1e-07, "amsgrad": false}}}}2
� root.layer_with_weights-0"_tf_keras_layer*�
-{"name": "conv2d", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": {"class_name": "__tuple__", "items": [null, 128, 44, 1]}, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Conv2D", "config": {"name": "conv2d", "trainable": true, "dtype": "float32", "batch_input_shape": {"class_name": "__tuple__", "items": [null, 128, 44, 1]}, "filters": 32, "kernel_size": {"class_name": "__tuple__", "items": [3, 3]}, "strides": {"class_name": "__tuple__", "items": [1, 1]}, "padding": "valid", "data_format": "channels_last", "dilation_rate": {"class_name": "__tuple__", "items": [1, 1]}, "groups": 1, "activation": "relu", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 2}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 3, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 4, "axes": {"-1": 1}}, "shared_object_id": 29}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 128, 44, 1]}}2
+{"name": "conv2d", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": {"class_name": "__tuple__", "items": [null, 128, 44, 1]}, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Conv2D", "config": {"name": "conv2d", "trainable": true, "batch_input_shape": {"class_name": "__tuple__", "items": [null, 128, 44, 1]}, "dtype": "float32", "filters": 32, "kernel_size": {"class_name": "__tuple__", "items": [3, 3]}, "strides": {"class_name": "__tuple__", "items": [1, 1]}, "padding": "valid", "data_format": "channels_last", "dilation_rate": {"class_name": "__tuple__", "items": [1, 1]}, "groups": 1, "activation": "relu", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 2}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 3, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 4, "axes": {"-1": 1}}, "shared_object_id": 29}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 128, 44, 1]}}2
� root.layer-1"_tf_keras_layer*�{"name": "max_pooling2d", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "MaxPooling2D", "config": {"name": "max_pooling2d", "trainable": true, "dtype": "float32", "pool_size": {"class_name": "__tuple__", "items": [2, 2]}, "padding": "valid", "strides": {"class_name": "__tuple__", "items": [2, 2]}, "data_format": "channels_last"}, "shared_object_id": 4, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": 4, "max_ndim": null, "min_ndim": null, "axes": {}}, "shared_object_id": 30}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 126, 42, 32]}}2
� root.layer-2"_tf_keras_layer*�{"name": "dropout", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Dropout", "config": {"name": "dropout", "trainable": true, "dtype": "float32", "rate": 0.2, "noise_shape": null, "seed": null}, "shared_object_id": 5, "build_input_shape": {"class_name": "TensorShape", "items": [null, 63, 21, 32]}}2
�
@@ -16,5 +16,5 @@
root.layer-9"_tf_keras_layer*�{"name": "dropout_2", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Dropout", "config": {"name": "dropout_2", "trainable": true, "dtype": "float32", "rate": 0.2, "noise_shape": null, "seed": null}, "shared_object_id": 18, "build_input_shape": {"class_name": "TensorShape", "items": [null, 64]}}2
� root.layer_with_weights-4"_tf_keras_layer*�{"name": "dense_1", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Dense", "config": {"name": "dense_1", "trainable": true, "dtype": "float32", "units": 32, "activation": "relu", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 19}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 20}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 21, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 2, "axes": {"-1": 64}}, "shared_object_id": 36}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 64]}}2
� root.layer_with_weights-5"_tf_keras_layer*�{"name": "dense_2", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Dense", "config": {"name": "dense_2", "trainable": true, "dtype": "float32", "units": 4, "activation": "softmax", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 22}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 23}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 24, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 2, "axes": {"-1": 32}}, "shared_object_id": 37}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 32]}}2
-��root.keras_api.metrics.0"_tf_keras_metric*�{"class_name": "Mean", "name": "loss", "dtype": "float32", "config": {"name": "loss", "dtype": "float32"}, "shared_object_id": 38}2
-��root.keras_api.metrics.1"_tf_keras_metric*�{"class_name": "MeanMetricWrapper", "name": "accuracy", "dtype": "float32", "config": {"name": "accuracy", "dtype": "float32", "fn": "sparse_categorical_accuracy"}, "shared_object_id": 28}2
\ No newline at end of file
+��root.keras_api.metrics.0"_tf_keras_metric*�{"class_name": "Mean", "name": "loss", "dtype": "float32", "config": {"name": "loss", "dtype": "float32"}, "shared_object_id": 38}2
+��root.keras_api.metrics.1"_tf_keras_metric*�{"class_name": "MeanMetricWrapper", "name": "accuracy", "dtype": "float32", "config": {"name": "accuracy", "dtype": "float32", "fn": "sparse_categorical_accuracy"}, "shared_object_id": 28}2
\ No newline at end of file
diff --git a/myproject/models/instrument_model/1/saved_model.pb b/myproject/models/instrument_model/1/saved_model.pb
index 17ff0d94c083b07b5eb7f1a9348cfb36fa15d532..334a4f1e41dcb57d38aabfc36e2e0af32608617f 100644
Binary files a/myproject/models/instrument_model/1/saved_model.pb and b/myproject/models/instrument_model/1/saved_model.pb differ
diff --git a/myproject/models/instrument_model/1/variables/variables.data-00000-of-00001 b/myproject/models/instrument_model/1/variables/variables.data-00000-of-00001
index ad1698fc39af144e83ea1bf207d1908eb51d22c4..6535da5d890975b1eaa6fc5060823c7a6d1018ed 100644
Binary files a/myproject/models/instrument_model/1/variables/variables.data-00000-of-00001 and b/myproject/models/instrument_model/1/variables/variables.data-00000-of-00001 differ
diff --git a/myproject/models/instrument_model/1/variables/variables.index b/myproject/models/instrument_model/1/variables/variables.index
index 6a8d3e1a107e9ba3b6a210b1af5d176f97f9ef14..28f23f1867b3715a930109b4857a14a0756441ef 100644
Binary files a/myproject/models/instrument_model/1/variables/variables.index and b/myproject/models/instrument_model/1/variables/variables.index differ
diff --git a/myproject/myapp/migrations/0002_modelconfig.py b/myproject/myapp/migrations/0002_modelconfig.py
new file mode 100644
index 0000000000000000000000000000000000000000..cc16f7a5eda2b34e9d8219d77e9c5c2820e59a04
--- /dev/null
+++ b/myproject/myapp/migrations/0002_modelconfig.py
@@ -0,0 +1,20 @@
+# Generated by Django 5.0.1 on 2024-04-30 23:25
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+ dependencies = [
+ ('myapp', '0001_initial'),
+ ]
+
+ operations = [
+ migrations.CreateModel(
+ name='ModelConfig',
+ fields=[
+ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+ ('selected_model_version', models.CharField(default='2', max_length=255)),
+ ],
+ ),
+ ]
diff --git a/myproject/myapp/migrations/0003_modelperformancemetrics.py b/myproject/myapp/migrations/0003_modelperformancemetrics.py
new file mode 100644
index 0000000000000000000000000000000000000000..bbaaf929c12d6ca636204521578361f546fef8ba
--- /dev/null
+++ b/myproject/myapp/migrations/0003_modelperformancemetrics.py
@@ -0,0 +1,25 @@
+# Generated by Django 5.0.1 on 2024-05-01 00:07
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+ dependencies = [
+ ('myapp', '0002_modelconfig'),
+ ]
+
+ operations = [
+ migrations.CreateModel(
+ name='ModelPerformanceMetrics',
+ fields=[
+ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+ ('request_count', models.IntegerField(default=0)),
+ ('request_latency_sum', models.FloatField(default=0)),
+ ('request_latency_count', models.IntegerField(default=0)),
+ ('runtime_latency_sum', models.FloatField(default=0)),
+ ('runtime_latency_count', models.IntegerField(default=0)),
+ ('model_load_latency', models.FloatField(default=0)),
+ ],
+ ),
+ ]
diff --git a/myproject/myapp/migrations/0004_payment.py b/myproject/myapp/migrations/0004_payment.py
new file mode 100644
index 0000000000000000000000000000000000000000..1e06945e7015f4dbcd1d774d1e6e1b6a4c2a2b61
--- /dev/null
+++ b/myproject/myapp/migrations/0004_payment.py
@@ -0,0 +1,27 @@
+# Generated by Django 5.0.1 on 2024-05-01 00:39
+
+import django.db.models.deletion
+from django.conf import settings
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+ dependencies = [
+ ('myapp', '0003_modelperformancemetrics'),
+ migrations.swappable_dependency(settings.AUTH_USER_MODEL),
+ ]
+
+ operations = [
+ migrations.CreateModel(
+ name='Payment',
+ fields=[
+ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+ ('amount', models.DecimalField(decimal_places=2, max_digits=10)),
+ ('payment_id', models.CharField(max_length=255)),
+ ('payer_id', models.CharField(max_length=255)),
+ ('date', models.DateTimeField(auto_now_add=True)),
+ ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
+ ],
+ ),
+ ]
diff --git a/myproject/myapp/models.py b/myproject/myapp/models.py
index 326123a737d7ef7aca00446c56a78ff39684017b..a67236e7fa208922c551b56bb7d1b251c14fd2ff 100644
--- a/myproject/myapp/models.py
+++ b/myproject/myapp/models.py
@@ -57,3 +57,43 @@ class Log(models.Model):
log = models.JSONField()
feedback = models.BooleanField(null=True)
+class ModelConfig(models.Model):
+ selected_model_version = models.CharField(max_length=255, default='2')
+
+ def save(self, *args, **kwargs):
+ # Ensure there's only one instance of ModelConfig
+ self.pk = 1
+ super().save(*args, **kwargs)
+
+ @classmethod
+ def load(cls):
+ obj, _ = cls.objects.get_or_create(pk=1)
+ return obj
+
+class ModelPerformanceMetrics(models.Model):
+ request_count = models.IntegerField(default=0)
+ request_latency_sum = models.FloatField(default=0)
+ request_latency_count = models.IntegerField(default=0)
+ runtime_latency_sum = models.FloatField(default=0)
+ runtime_latency_count = models.IntegerField(default=0)
+ model_load_latency = models.FloatField(default=0)
+
+ def reset_metrics(self):
+ self.request_count = 0
+ self.request_latency_sum = 0
+ self.request_latency_count = 0
+ self.runtime_latency_sum = 0
+ self.runtime_latency_count = 0
+ self.model_load_latency = 0
+ self.save(force_update=True)
+
+class Payment(models.Model):
+ user = models.ForeignKey(User, on_delete=models.CASCADE)
+ amount = models.DecimalField(max_digits=10, decimal_places=2)
+ payment_id = models.CharField(max_length=255)
+ payer_id = models.CharField(max_length=255)
+ date = models.DateTimeField(auto_now_add=True)
+
+ def __str__(self):
+ return f'Payment by {self.user.username} - Amount: {self.amount}'
+
diff --git a/myproject/myapp/payments.py b/myproject/myapp/payments.py
index dd8e0026c63867cf88788ec2b0979647e3b6c11b..b1108fd9e985622974b0b69dfa042f426da12ac8 100644
--- a/myproject/myapp/payments.py
+++ b/myproject/myapp/payments.py
@@ -5,6 +5,7 @@ from django.shortcuts import redirect, render
from django.urls import reverse
from django.shortcuts import redirect, render
from django.urls import reverse
+from .models import Action, UserTokenCount, Payment
from .views import get_log_data, create_log
from .models import UserTokenCount, Action
from rest_framework.response import Response
@@ -82,12 +83,56 @@ def create_payment(request, purchase_type):
# Execute a successful payment
+# def execute_payment(request):
+# # Get payment id and payer id
+# payment_id = request.GET.get('paymentId')
+# payer_id = request.GET.get('PayerID')
+
+# #If neither ID, error, restart
+# if not payment_id or not payer_id:
+# print("no payment")
+# #TODO: Change this to a more appropriate path, maybe a generic error page that takes a string:Error to display in a template
+# return redirect('handler404')
+
+# # configure API
+# paypalrestsdk.configure({
+# "mode": settings.PAYPAL_MODE,
+# "client_id": settings.PAYPAL_CLIENT_ID,
+# "client_secret": settings.PAYPAL_CLIENT_SECRET
+# })
+
+# # Check we've got a successful payment
+# payment = paypalrestsdk.Payment.find(payment_id)
+
+# # If it we do an the payer IDs match
+# if payment.execute({"payer_id": payer_id}):
+# print("Payment executed successfully!")
+
+# # Allocate some tokens
+# user = request.user
+# tokens_purchased = 1
+
+# # increment user_tokens
+# # commit changes
+# # TODO: Change something here such that the token amount added depends on a detail of the transaction,
+# # i.e. £9.99 payment for one token or £24.99 for
+# #
+# if request.user.is_authenticated:
+# add_tokens(user, tokens_purchased)
+# return redirect('success')
+# else:
+# return redirect('handler404')
+# else:
+# #TODO: Change this to a more appropriate error message
+# print("exiting at the end of execute_payment()")
+# return redirect('handler404')
+
def execute_payment(request):
# Get payment id and payer id
payment_id = request.GET.get('paymentId')
payer_id = request.GET.get('PayerID')
- #If neither ID, error, restart
+ # If neither ID, error, restart
if not payment_id or not payer_id:
print("no payment id or payer_id")
return Response({"error": "Error: No payment id or payer id was found."}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
@@ -102,7 +147,7 @@ def execute_payment(request):
# Check we've got a successful payment
payment = paypalrestsdk.Payment.find(payment_id)
- # If it we do an the payer IDs match
+ # If it we do and the payer IDs match
if payment.execute({"payer_id": payer_id}):
print("Payment executed successfully!")
print(f"Payment: {payment}")
@@ -124,7 +169,6 @@ def execute_payment(request):
print("exiting at the end of execute_payment(), incorrect payer id")
return Response({"error": "Error: Payment failed to execute, incorrect payer id"}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
-
def add_tokens(user, tokens):
token_count_instance, created = UserTokenCount.objects.get_or_create(user=user)
token_count_instance.token_count += int(tokens)
diff --git a/myproject/myapp/templates/model_performance.html b/myproject/myapp/templates/model_performance.html
index 493a96fefbcdd6400b46e9557fba667aa6001aae..30d0227a9162012986db987ee01335e57d991cd3 100644
--- a/myproject/myapp/templates/model_performance.html
+++ b/myproject/myapp/templates/model_performance.html
@@ -1,18 +1,26 @@
+<!-- model_performance.html -->
{% extends "_base.html" %}
{% block content %}
<div class="container mx-auto px-4">
- <h1 class="text-2xl font-bold mb-4">Model Performance</h1>
-
- {% if metrics %}
+ <h1 class="text-2xl font-bold mb-4">Model Performance</h1>
+
+ {% if metrics %}
<div class="bg-white shadow-md rounded p-6">
- <p><strong>Request Count:</strong> {{ metrics.request_count }}</p>
- <p><strong>Average Request Latency:</strong> {{ metrics.avg_request_latency|floatformat:6 }} seconds</p>
- <p><strong>Average Runtime Latency:</strong> {{ metrics.avg_runtime_latency|floatformat:6 }} seconds</p>
- <p><strong>Model Load Latency:</strong> {{ metrics.model_load_latency|floatformat:6 }} seconds</p>
+ <p><strong>Request Count:</strong> {{ metrics.request_count }}</p>
+ <p><strong>Average Request Latency:</strong> {{ metrics.avg_request_latency|floatformat:6 }} seconds</p>
+ <p><strong>Average Runtime Latency:</strong> {{ metrics.avg_runtime_latency|floatformat:6 }} seconds</p>
+ <p><strong>Model Load Latency:</strong> {{ metrics.model_load_latency|floatformat:6 }} seconds</p>
</div>
- {% else %}
+ {% else %}
<p>Failed to retrieve model performance metrics.</p>
- {% endif %}
+ {% endif %}
+
+ <form method="post" action="{% url 'model_performance' %}" class="mt-4">
+ {% csrf_token %}
+ <button type="submit" name="reset_metrics" class="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded">
+ Reset Metrics
+ </button>
+ </form>
</div>
{% endblock content %}
\ No newline at end of file
diff --git a/myproject/myapp/templates/model_selection.html b/myproject/myapp/templates/model_selection.html
new file mode 100644
index 0000000000000000000000000000000000000000..d14c882f552a27e1260ecb0641f247918004229b
--- /dev/null
+++ b/myproject/myapp/templates/model_selection.html
@@ -0,0 +1,15 @@
+{% extends '_base.html' %}
+
+{% block content %}
+ <h1>Model Version Selection</h1>
+ <form method="post">
+ {% csrf_token %}
+ <label for="model_version">Select Model Version:</label>
+ <select name="model_version" id="model_version">
+ {% for version in model_versions %}
+ <option value="{{ version }}" {% if selected_model_version == version %}selected{% endif %}>{{ version }}</option>
+ {% endfor %}
+ </select>
+ <button type="submit">Save</button>
+ </form>
+{% endblock %}
\ No newline at end of file
diff --git a/myproject/myapp/templates/user_page.html b/myproject/myapp/templates/user_page.html
index 94fff4c7e67ee2c07c291645b76abd1283521393..987c029969c603ccae4006aaed7ba29cd5c26af4 100644
--- a/myproject/myapp/templates/user_page.html
+++ b/myproject/myapp/templates/user_page.html
@@ -1,4 +1,6 @@
-{% extends "_base.html" %} {% block content %}
+<!-- user_page.html -->
+{% extends "_base.html" %}
+{% block content %}
<div
class="grid grid-cols-1 px-4 pt-6 xl:grid-cols-3 xl:gap-4 dark:bg-grey-300"
>
@@ -33,7 +35,13 @@
<h3 class="mb-4 text-xl font-semibold dark:text-white">Change your password</h3>
<a href="{% url 'password_change' %}" class="text-white bg-blue-700 hover:bg-blue-800 focus:ring-4 focus:ring-blue-300 font-medium rounded-lg text-sm px-5 py-2.5 text-center dark:bg-blue-600 dark:hover:bg-blue-700 dark:focus:ring-blue-800">Change Password</a>
</div>
-
+
+ {% if user_profile.user_type == 2 or user.is_superuser %}
+ <div class="p-4 mb-4 bg-white border border-gray-200 rounded-lg shadow-sm 2xl:col-span-2 dark:border-gray-700 sm:p-6 dark:bg-gray-800">
+ <h3 class="mb-4 text-xl font-semibold dark:text-white">Model Selection</h3>
+ <a href="{% url 'model_selection' %}" class="text-white bg-blue-700 hover:bg-blue-800 focus:ring-4 focus:ring-blue-300 font-medium rounded-lg text-sm px-5 py-2.5 text-center dark:bg-blue-600 dark:hover:bg-blue-700 dark:focus:ring-blue-800">Select Model</a>
+ </div>
+ {% endif %}
{% if user_profile.user_type == 3 or user.is_superuser or user_profile.user_type == 1%}
<div
diff --git a/myproject/myapp/urls.py b/myproject/myapp/urls.py
index 6a58000925a139ce144b37b3bffe66981948f90a..a7c38d019e636e988f655430977fb3a3eca36243 100644
--- a/myproject/myapp/urls.py
+++ b/myproject/myapp/urls.py
@@ -1,5 +1,5 @@
from django.urls import path
-from .views import InstrumentDetectionView, ModelPerformanceView, index, log_fileupload, users, maintenance, \
+from .views import InstrumentDetectionView, ModelPerformanceView, ModelSelectionView, index, log_fileupload, users, maintenance, \
handler404, handler500, terms_conditions, privacy_policy, pricing, generate_pdf, admin_table,\
change_user_type, submit_feedback
from .payments import create_payment, execute_payment, payment_cancelled, payment_success
@@ -26,6 +26,7 @@ urlpatterns = [
path('generate_pdf/', generate_pdf, name='generate_pdf'),
path('instrument_detection/', InstrumentDetectionView.as_view(), name='instrument_detection'),
path('model_performance/', ModelPerformanceView.as_view(), name='model_performance'),
+ path('model_selection/', ModelSelectionView.as_view(), name='model_selection'),
path('password_change/', auth_views.PasswordChangeView.as_view(template_name='password_change_form.html'), name='password_change'),
path('password_change/done/', auth_views.PasswordChangeDoneView.as_view(template_name='password_change_done.html'), name='password_change_done'),
diff --git a/myproject/myapp/views.py b/myproject/myapp/views.py
index f89359211c1c844ac595562a1a452dee9ecffbd0..e65ac6c9f5be9c7e24b166b5748322c5aaa0721a 100644
--- a/myproject/myapp/views.py
+++ b/myproject/myapp/views.py
@@ -1,3 +1,5 @@
+# views.py
+import os
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth.models import User
@@ -12,7 +14,7 @@ import json
from datetime import datetime
from .forms import InstrumentDetectionForm
-from .models import Log, Action, User, UserTokenCount, Profile
+from .models import Log, Action, User, UserTokenCount, Profile, ModelConfig, ModelPerformanceMetrics
from django.http import JsonResponse
from django.db import connection
@@ -26,8 +28,8 @@ import requests
# Authentication Imports
from django.urls import reverse_lazy
-from django.views import generic
-from .models import Profile
+from django.views import View, generic
+from .models import Profile, ModelConfig
from .forms import UserRegisterForm, LoginAuthenticationForm
from django.contrib.auth.views import LoginView
from django.views.decorators.csrf import csrf_exempt
@@ -370,42 +372,50 @@ class InstrumentDetectionView(APIView):
else: return super().dispatch(request, *args, **kwargs)
def post(self, request):
- # Get the user's token count
- user_token_count = UserTokenCount.objects.get(user=request.user)
-
- # Decrease the user's token count by one
- user_token_count.token_count -= 1
- user_token_count.save()
-
- serializer = InstrumentDetectionSerializer(data=request.data)
- if serializer.is_valid():
- audio_file = serializer.validated_data['audio_file']
-
- # Save the uploaded file temporarily
- # with open('temp_audio.wav', 'wb') as f:
- # f.write(audio_file.read())
-
- # Preprocess the audio file
- preprocessed_data = preprocess_audio_for_inference(audio_file)
-
- # Prepare data for TensorFlow Serving
- data = json.dumps({"signature_name": "serving_default", "instances": [window.tolist() for window in preprocessed_data]})
-
- # Send request to TensorFlow Serving
- url = 'http://tensorflow_serving:8501/v1/models/instrument_model/versions/2:predict'
- headers = {"Content-Type": "application/json"}
- response = requests.post(url, data=data, headers=headers)
-
- # Process the response
- if response.status_code == 200:
- raw_predictions = response.json()['predictions']
- # Convert raw prediction numbers into percentages
- formatted_predictions = self.format_predictions(raw_predictions)
- return Response({"predictions": formatted_predictions}, status=status.HTTP_200_OK)
- else:
- return Response({"error": "Failed to get predictions"}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
-
- return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
+ try:
+ model_config = ModelConfig.load()
+ selected_model_version = model_config.selected_model_version
+ # Get the user's token count
+ user_token_count = UserTokenCount.objects.get(user=request.user)
+
+ # Decrease the user's token count by one
+ user_token_count.token_count -= 1
+ user_token_count.save()
+
+ serializer = InstrumentDetectionSerializer(data=request.data)
+ if serializer.is_valid():
+ audio_file = serializer.validated_data['audio_file']
+
+ # Save the uploaded file temporarily
+ # with open('temp_audio.wav', 'wb') as f:
+ # f.write(audio_file.read())
+
+ # Preprocess the audio file
+ preprocessed_data = preprocess_audio_for_inference(audio_file)
+
+ # Prepare data for TensorFlow Serving
+ data = json.dumps({"signature_name": "serving_default", "instances": [window.tolist() for window in preprocessed_data]})
+
+ # Send request to TensorFlow Serving
+ # url = 'http://tensorflow_serving:8501/v1/models/instrument_model/versions/2:predict'
+ url = f'http://tensorflow_serving:8501/v1/models/instrument_model/versions/{selected_model_version}:predict'
+ headers = {"Content-Type": "application/json"}
+ response = requests.post(url, data=data, headers=headers)
+
+ # Process the response
+ if response.status_code == 200:
+ print('Predictions received')
+ raw_predictions = response.json()['predictions']
+ # Convert raw prediction numbers into percentages
+ formatted_predictions = self.format_predictions(raw_predictions)
+ return Response({"predictions": formatted_predictions}, status=status.HTTP_200_OK)
+ else:
+ return Response({"error": "Failed to get predictions"}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+ except Exception as e:
+ logger.error(f"An error occurred: {e}")
+ messages.error(request, 'An error occurred: {e}')
+ return redirect('index')
def format_predictions(self, predictions):
@@ -433,10 +443,10 @@ class ModelPerformanceView(UserPassesTestMixin, TemplateView):
def dispatch(self, request, *args, **kwargs):
if request.user.is_anonymous:
- messages.info(request, 'Must be logged in as an ML Engineer or Admin to access this page.')
+ messages.info(request, 'Must be logged in as an ML Engineer or Superuser to access this page.')
return redirect('login')
elif request.user.profile.user_type != 2 and not request.user.is_superuser:
- messages.info(request, 'Must be logged in as an ML Engineer or Admin to access this page.')
+ messages.info(request, 'Must be logged in as an ML Engineer or Superuser to access this page.')
return redirect('users')
else:
return super().dispatch(request, *args, **kwargs)
@@ -461,21 +471,73 @@ class ModelPerformanceView(UserPassesTestMixin, TemplateView):
runtime_latency_count = re.search(r':tensorflow:serving:runtime_latency_count{model_name="instrument_model",API="Predict",runtime="TF1"} (\d+)', metrics_data)
model_load_latency = re.search(r':tensorflow:cc:saved_model:load_latency{model_path="/models/instrument_model/2"} (\d+)', metrics_data)
+ # Get or create the ModelPerformanceMetrics instance
+ metrics, _ = ModelPerformanceMetrics.objects.get_or_create(pk=1)
+
+ # Update the metrics in the database
+ metrics.request_count = int(request_count.group(1)) if request_count else 0
+ metrics.request_latency_sum = float(request_latency_sum.group(1)) if request_latency_sum else 0
+ metrics.request_latency_count = int(request_latency_count.group(1)) if request_latency_count else 0
+ metrics.runtime_latency_sum = float(runtime_latency_sum.group(1)) if runtime_latency_sum else 0
+ metrics.runtime_latency_count = int(runtime_latency_count.group(1)) if runtime_latency_count else 0
+ metrics.model_load_latency = float(model_load_latency.group(1)) if model_load_latency else 0
+ metrics.save()
+
# Calculate average latencies in seconds
- avg_request_latency = float(request_latency_sum.group(1)) / float(request_latency_count.group(1)) / 1e6 if request_latency_sum and request_latency_count else None
- avg_runtime_latency = float(runtime_latency_sum.group(1)) / float(runtime_latency_count.group(1)) / 1e6 if runtime_latency_sum and runtime_latency_count else None
- model_load_latency_seconds = float(model_load_latency.group(1)) / 1e6 if model_load_latency else None
+ avg_request_latency = metrics.request_latency_sum / metrics.request_latency_count / 1e6 if metrics.request_latency_count else None
+ avg_runtime_latency = metrics.runtime_latency_sum / metrics.runtime_latency_count / 1e6 if metrics.runtime_latency_count else None
context['metrics'] = {
- 'request_count': request_count.group(1) if request_count else None,
+ 'request_count': metrics.request_count,
'avg_request_latency': avg_request_latency,
'avg_runtime_latency': avg_runtime_latency,
- 'model_load_latency': model_load_latency_seconds
+ 'model_load_latency': metrics.model_load_latency / 1e6
}
else:
context['metrics'] = None
return context
+ def post(self, request, *args, **kwargs):
+ if 'reset_metrics' in request.POST:
+ metrics = ModelPerformanceMetrics.objects.get(pk=1)
+ metrics.reset_metrics()
+ metrics.save()
+ return redirect('users')
+ else:
+ messages.error(request, 'Invalid request')
+ return redirect('users')
+
+class ModelSelectionView(UserPassesTestMixin, View):
+ def dispatch(self, request, *args, **kwargs):
+ if request.user.is_anonymous:
+ messages.info(request, 'Must be logged in as an ML Engineer or Superuser to access this page.')
+ return redirect('login')
+ elif request.user.profile.user_type != 2 and not request.user.is_superuser:
+ messages.info(request, 'Must be logged in as an ML Engineer or Superuser to access this page.')
+ return redirect('users')
+ else:
+ return super().dispatch(request, *args, **kwargs)
+
+ def test_func(self):
+ return self.request.user.is_authenticated and self.request.user.profile.user_type == 2
+
+ def get(self, request):
+ model_versions = os.listdir('models/instrument_model')
+ model_config = ModelConfig.load()
+ context = {
+ 'model_versions': model_versions,
+ 'selected_model_version': model_config.selected_model_version,
+ }
+ return render(request, 'model_selection.html', context)
+
+ def post(self, request):
+ selected_model_version = request.POST.get('model_version')
+ model_config = ModelConfig.load()
+ model_config.selected_model_version = selected_model_version
+ model_config.save()
+ return redirect('model_selection')
+
+
def change_user_type(request, user_id):
if request.method == 'POST':
@@ -487,7 +549,4 @@ def change_user_type(request, user_id):
def user_has_credits():
has_credits = False
-
-
-
return has_credits