{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyMZU9NIL9Z+tmzB6E63g064"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["## Pengenalan Tensor\n","Tensor adalah struktur data utama dalam TensorFlow dan PyTorch. Mirip dengan array atau matriks, tensor bisa memiliki dimensi lebih tinggi, misalnya 3D, 4D, dan seterusnya. Berikut adalah operasi dasar dengan tensor."],"metadata":{"id":"KryTJ4bT_TPf"}},{"cell_type":"markdown","source":["## TensorFlow vs. PyTorch\n","\n","*   TensorFlow: Dikembangkan oleh Google, TensorFlow sering digunakan untuk produksi model skala besar. TensorFlow memiliki lebih banyak fitur terintegrasi untuk deployment.\n","*   PyTorch: Dikembangkan oleh Facebook, PyTorch populer di kalangan peneliti karena pendekatannya yang lebih intuitif dan dinamis."],"metadata":{"id":"yZZq8D_x_YXQ"}},{"cell_type":"markdown","source":["## Instalasi PyTorch\n","`!pip install torch torchvision`"],"metadata":{"id":"VxE-qr32_loc"}},{"cell_type":"code","execution_count":1,"metadata":{"id":"pYKyitXt_E0M","executionInfo":{"status":"ok","timestamp":1724026664038,"user_tz":-420,"elapsed":6454,"user":{"displayName":"Andys Collection","userId":"04951959771200949138"}}},"outputs":[],"source":["import torch"]},{"cell_type":"code","source":["# Membuat tensor 2x3\n","tensor_pt = torch.tensor([[1, 2, 3], [4, 5, 6]])\n","print(tensor_pt)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hp716GSk_2YB","executionInfo":{"status":"ok","timestamp":1724026689486,"user_tz":-420,"elapsed":520,"user":{"displayName":"Andys Collection","userId":"04951959771200949138"}},"outputId":"7ed75221-1dcb-4ff4-dca1-dee564bf5c25"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([[1, 2, 3],\n","        [4, 5, 6]])\n"]}]},{"cell_type":"markdown","source":["## Operasi Dasar dengan Tensor\n","Setelah kita punya tensor, kita bisa melakukan operasi dasar seperti penambahan, pengurangan, perkalian, dan sebagainya."],"metadata":{"id":"erAxdfR3_9h0"}},{"cell_type":"code","source":["# Penambahan\n","add_result = tensor_pt + 2\n","print(add_result)\n","\n","# Perkalian elemen-wise\n","mul_result = tensor_pt * 3\n","print(mul_result)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1rPZY2D8ACwu","executionInfo":{"status":"ok","timestamp":1724026731421,"user_tz":-420,"elapsed":525,"user":{"displayName":"Andys Collection","userId":"04951959771200949138"}},"outputId":"d494d3e0-764f-4a2e-b872-413432cbf69f"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([[3, 4, 5],\n","        [6, 7, 8]])\n","tensor([[ 3,  6,  9],\n","        [12, 15, 18]])\n"]}]},{"cell_type":"markdown","source":["## Menggunakan GPU\n","Baik TensorFlow maupun PyTorch mendukung penggunaan GPU untuk mempercepat komputasi:"],"metadata":{"id":"AZxl8k73AQol"}},{"cell_type":"code","source":["device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n","tensor_pt = tensor_pt.to(device)\n","result = tensor_pt * 2\n","print(result)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"A3QZWZg4AP-E","executionInfo":{"status":"ok","timestamp":1724026804678,"user_tz":-420,"elapsed":488,"user":{"displayName":"Andys Collection","userId":"04951959771200949138"}},"outputId":"da31eaa6-0bd0-4ece-8e9d-57096b11b2a3"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([[ 2,  4,  6],\n","        [ 8, 10, 12]])\n"]}]}]}